<reponame>jackie930/PyABSA<filename>demos/aspect_polarity_classification/expriments/main/run_LSA-ETA_exp.py
# -*- coding: utf-8 -*-
# file: run_LSA-ETA_exp.py
# time: 2021/11/21
# author: yangheng <<EMAIL>>
# github: https://github.com/yangheng95
# Copyright (C) 2021. All Rights Reserved.


########################################################################################################################
#                    train and evaluate on your own apc_datasets (need train and test apc_datasets)                    #
########################################################################################################################
import random

from pyabsa.functional import Trainer
from pyabsa.functional import APCConfigManager
from pyabsa.functional import ABSADatasetList
from pyabsa.functional import APCModelList

seeds = [random.randint(0, 10000) for _ in range(1)]


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.1
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.2
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.3
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.4
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.5
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.6
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.7
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.8
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.9
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 1
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.1
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.2
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.3
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.4
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.5
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.6
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.7
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.8
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.9
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 1
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()
# -*- coding: utf-8 -*-
# file: run_LSA-ETA_exp.py
# time: 2021/11/21
# author: yangheng <<EMAIL>>
# github: https://github.com/yangheng95
# Copyright (C) 2021. All Rights Reserved.


########################################################################################################################
#                    train and evaluate on your own apc_datasets (need train and test apc_datasets)                    #
########################################################################################################################
import random

from pyabsa.functional import Trainer
from pyabsa.functional import APCConfigManager
from pyabsa.functional import ABSADatasetList
from pyabsa.functional import APCModelList

seeds = [random.randint(0, 10000) for _ in range(1)]


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.1
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.2
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.3
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.4
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.5
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.6
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.7
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.8
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.9
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_S
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 1
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.1
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.2
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.3
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.4
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.5
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.6
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.7
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.8
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 0.9
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()


apc_config_english = APCConfigManager.get_apc_config_english()
apc_config_english.model = APCModelList.FAST_FAST_LSA_T
apc_config_english.lcf = 'cdw'
apc_config_english.similarity_threshold = 1
apc_config_english.max_seq_len = 80
apc_config_english.eta = 1
apc_config_english.dropout = 0
apc_config_english.cache_dataset = False
apc_config_english.log_step = 5
apc_config_english.pretrained_bert = 'microsoft/deberta-v3-base'
apc_config_english.hidden_dim = 768
apc_config_english.embed_dim = 768
apc_config_english.num_epoch = 25
apc_config_english.learning_rate = 1e-5
apc_config_english.batch_size = 16
apc_config_english.evaluate_begin = 5
apc_config_english.l2reg = 0.00001
apc_config_english.seed = seeds
apc_config_english.cross_validate_fold = -1  # disable cross_validate

Laptop14 = ABSADatasetList.Laptop14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Laptop14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant14 = ABSADatasetList.Restaurant14
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant14,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant15 = ABSADatasetList.Restaurant15
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant15,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()

Restaurant16 = ABSADatasetList.Restaurant16
sent_classifier = Trainer(config=apc_config_english,
                          dataset=Restaurant16,  # train set and test set will be automatically detected
                          checkpoint_save_mode=0,  # =None to avoid save model
                          auto_device=True  # automatic choose CUDA or CPU
                          ).load_trained_model()
# -*- coding: utf-8 -*- # file: run_LSA-ETA_exp.py # time: 2021/11/21 # author: yangheng <<EMAIL>> # github: https://github.com/yangheng95 # Copyright (C) 2021. All Rights Reserved. ######################################################################################################################## #                    train and evaluate on your own apc_datasets (need train and test apc_datasets)                    # ######################################################################################################################## # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # disable cross_validate # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU # train set and test set will be automatically detected # =None to avoid save model # automatic choose CUDA or CPU