Spaces:
Runtime error
Runtime error
File size: 1,556 Bytes
3b96cb1 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 |
# Copyright (c) OpenMMLab. All rights reserved.
# This is a BETA new format config file, and the usage may change recently.
from mmengine.config import read_base
with read_base():
from ..._base_.datasets.imagenet_bs64_swin_224 import *
from ..._base_.schedules.imagenet_bs1024_adamw_swin import *
from ..._base_.default_runtime import *
from mmengine.model import ConstantInit, TruncNormalInit
from mmpretrain.models import (BEiTViT, ImageClassifier, LabelSmoothLoss,
LinearClsHead)
from mmpretrain.models.utils.batch_augments import CutMix, Mixup
data_preprocessor = dict(
num_classes=1000,
# RGB format normalization parameters
mean=[127.5, 127.5, 127.5],
std=[127.5, 127.5, 127.5],
# convert image from BGR to RGB
to_rgb=True,
)
model = dict(
type=ImageClassifier,
backbone=dict(
type=BEiTViT,
arch='base',
img_size=224,
patch_size=16,
out_type='avg_featmap',
use_abs_pos_emb=False,
use_rel_pos_bias=True,
use_shared_rel_pos_bias=False,
),
neck=None,
head=dict(
type=LinearClsHead,
num_classes=1000,
in_channels=768,
loss=dict(type=LabelSmoothLoss, label_smooth_val=0.1, mode='original'),
),
init_cfg=[
dict(type=TruncNormalInit, layer='Linear', std=.02),
dict(type=ConstantInit, layer='LayerNorm', val=1., bias=0.),
],
train_cfg=dict(
augments=[dict(type=Mixup, alpha=0.8),
dict(type=CutMix, alpha=1.0)]))
|