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Types & classes37 in github.com/beyondguo/genius

⨍ Functions 284◇ Types & classes 37↳ Endpoints 1
↓ 8 callersClassSketchExtractor
genius_utils.py:26
↓ 5 callersClassAspectKeyBERT
aspect_keybert.py:20
↓ 5 callersClassList2Dataset
genius_utils.py:186
↓ 5 callersClassMyDataset
_backup_scripts/my_dataset.py:8
↓ 5 callersClassTextAugmenter
augmentation_clf/STA/text_augmenter.py:22
↓ 4 callersClassMyDataset
augmentation_clf/STA/my_dataset.py:28
↓ 4 callersClassMyDataset
_backup_scripts/qa_back_trans.py:45
↓ 4 callersClasscomposed_word
yake/datarepresentation.py:184
↓ 2 callersClassKeywordsExtractor
augmentation_clf/STA/keywords_extractor.py:91
↓ 2 callersClassMyDataset
utils.py:46
↓ 2 callersClassMyDataset
augmentation_clf/backtrans_clf.py:24
↓ 2 callersClassTextAugmenter
_backup_scripts/easy_text_augmenter.py:15
↓ 1 callersClassDataCore
yake/datarepresentation.py:14
↓ 1 callersClassK2T_Generator
_backup_scripts/ner_aug.py:181
↓ 1 callersClassK2T_Generator
_backup_scripts/run_qa_aug.py:10
↓ 1 callersClassK2T_Generator
_backup_scripts/run_aug.py:23
↓ 1 callersClassLabelPrefixTokenizedDataset
augmentation_clf/conditional_mlm_clf.py:75
↓ 1 callersClassList2Dataset
augmentation_clf/conditional_clm_clf.py:55
↓ 1 callersClassMDataset
_backup_scripts/k2t_new_ner_aug.py:200
↓ 1 callersClassMDataset
_backup_scripts/k2t_new_sm_aug.py:79
↓ 1 callersClassMyDataloaders
读取标准化csv数据集，自动划分验证集。 初始化参数：train_path, test_path, tokenizer, maxlen, bsz, collate_fn 对象的重要属性： unique_labels label2idx idx2lab
augmentation_clf/STA/my_dataset.py:53
↓ 1 callersClassMyTagger
_backup_scripts/ner_aug.py:197
↓ 1 callersClassMyTagger
_backup_scripts/k2t_new_ner_aug.py:216
↓ 1 callersClassMyTagger
augmentation_ner_qa/genius_ner_aug.py:85
↓ 1 callersClassOrderNamespace
utils.py:25
↓ 1 callersClassOrderNamespace
augmentation_clf/STA/utils.py:22
↓ 1 callersClassQuestionAnsweringTrainer
augmentation_ner_qa/trainer_qa.py:28
↓ 1 callersClassTokenizedDataset
augmentation_clf/mlm_clf.py:66
↓ 1 callersClasssingle_word
yake/datarepresentation.py:337
ClassDataTrainingArguments
Arguments pertaining to what data we are going to input our model for training and eval.
augmentation_ner_qa/run_qa.py:91
ClassKeywordExtractor
yake/yake.py:12
ClassLevenshtein
yake/Levenshtein.py:3
ClassModelArguments
Arguments pertaining to which model/config/tokenizer we are going to fine-tune from.
augmentation_ner_qa/run_qa.py:59
ClassMyDataloaders
读取标准化csv数据集，自动划分验证集。 初始化参数：train_path, test_path, tokenizer, maxlen, bsz, collate_fn 对象的重要属性： unique_labels label2idx idx2lab
_backup_scripts/my_dataset.py:37
ClassMyDataset
_backup_scripts/qa_aug_eda.py:36
ClassS2T_Dataset
_backup_scripts/s2t_utils.py:40
ClassTextHighlighter
yake/highlight.py:6