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Functions2,799 in github.com/CLUEbenchmark/CLUE

⨍ Functions 2,799◇ Types & classes 431
↓ 2 callersFunction_remove_checkpoint
(checkpoint_path)
baselines/models/roberta/run_classifier.py:912
↓ 2 callersFunction_sample_mask
Sample `goal_num_predict` tokens for partial prediction. About `mask_beta` tokens are chosen in a context of `mask_alpha` tokens.
baselines/models/xlnet/data_utils.py:331
↓ 2 callersFunction_strip_spaces
(text)
baselines/models_pytorch/mrc_pytorch/preprocess/cmrc2018_output.py:373
↓ 2 callersFunction_strip_spaces
(text)
baselines/models_pytorch/mrc_pytorch/preprocess/DRCD_output.py:371
↓ 2 callersFunction_strip_spaces
(text)
baselines/models/roberta_wwm_ext/run_squad.py:955
↓ 2 callersFunction_strip_spaces
(text)
baselines/models/ernie/run_squad.py:955
↓ 2 callersFunction_strip_spaces
(text)
baselines/models/bert_wwm_ext/run_squad.py:955
↓ 2 callersFunction_strip_spaces
(text)
baselines/models/roberta_wwm_large_ext/run_squad.py:955
↓ 2 callersFunction_strip_spaces
(text)
baselines/models/bert/run_squad.py:955
↓ 2 callersMethod_tie_or_clone_data
Tie or clone module weights depending of weither we are using TorchScript or not
baselines/models_pytorch/classifier_pytorch/transformers/modeling_utils.py:136
↓ 2 callersMethod_tokenize
Converts a string in a sequence of tokens (string), using the tokenizer. Split in words for word-based vocabulary or sub-words for sub-wo
baselines/models_pytorch/classifier_pytorch/transformers/tokenization_utils.py:652
↓ 2 callersFunction_tokenize_chinese_chars
Adds whitespace around any CJK character.
baselines/models_pytorch/mrc_pytorch/preprocess/DRCD_preprocess.py:132
↓ 2 callersFunction_truncate_seq_pair
Truncates a sequence pair in place to the maximum length.
baselines/models/roberta/run_classifier.py:489
↓ 2 callersFunction_truncate_seq_pair
Truncates a sequence pair in place to the maximum length.
baselines/models/albert/run_classifier.py:485
↓ 2 callersFunction_truncate_seq_pair
Truncates a sequence pair in place to the maximum length.
baselines/models/roberta_wwm_ext/run_classifier.py:484
↓ 2 callersFunction_truncate_seq_pair
Truncates a sequence pair in place to the maximum length.
baselines/models/ernie/run_classifier.py:484
↓ 2 callersFunction_truncate_seq_pair
Truncates a sequence pair in place to the maximum length.
baselines/models/bert_wwm_ext/run_classifier.py:484
↓ 2 callersFunction_truncate_seq_pair
Truncates a sequence pair in place to the maximum length.
baselines/models/roberta_wwm_large_ext/run_classifier.py:487
↓ 2 callersFunction_truncate_seq_pair
Truncates a sequence pair in place to the maximum length.
baselines/models/bert/run_classifier.py:485
↓ 2 callersFunction_truncate_seq_pair
Truncates a sequence pair in place to the maximum length.
baselines/models/xlnet/run_classifier.py:185
↓ 2 callersMethodadd_symbol
(self, sym)
baselines/models_pytorch/classifier_pytorch/transformers/tokenization_transfo_xl.py:213
↓ 2 callersMethodadd_tokens
Add a list of new tokens to the tokenizer class. If the new tokens are not in the vocabulary, they are added to it with indices start
baselines/models_pytorch/classifier_pytorch/transformers/tokenization_utils.py:488
↓ 2 callersMethodapply_gradients
See base class.
baselines/models/roberta_wwm_ext/optimization.py:108
↓ 2 callersMethodapply_gradients
See base class.
baselines/models/ernie/optimization.py:108
↓ 2 callersMethodapply_gradients
See base class.
baselines/models/bert_wwm_ext/optimization.py:108
↓ 2 callersMethodapply_gradients
See base class.
baselines/models/roberta_wwm_large_ext/optimization.py:108
↓ 2 callersMethodapply_gradients
See base class.
baselines/models/bert/optimization.py:108
↓ 2 callersFunctionapply_no_ans_threshold
(scores, na_probs, qid_to_has_ans, na_prob_thresh)
baselines/models/xlnet/squad_utils.py:102
↓ 2 callersFunctionattention_layer
Performs multi-headed attention from `from_tensor` to `to_tensor`. This is an implementation of multi-headed attention based on "Attention is all
baselines/models/albert/modeling.py:637
↓ 2 callersFunctionbatchify
(data, bsz_per_host, sent_ids=None)
baselines/models/xlnet/data_utils.py:242
↓ 2 callersMethodbpe
(self, token)
baselines/models_pytorch/classifier_pytorch/transformers/tokenization_openai.py:115
↓ 2 callersMethodbuild_inputs_with_special_tokens
Build model inputs from a sequence or a pair of sequence for sequence classification tasks by concatenating and adding special tokens
baselines/models_pytorch/classifier_pytorch/transformers/tokenization_utils.py:928
↓ 2 callersMethodbuild_vocab
(self)
baselines/models_pytorch/classifier_pytorch/transformers/tokenization_transfo_xl.py:155
↓ 2 callersFunctioncached_path
Given something that might be a URL (or might be a local path), determine which. If it's a URL, download the file and cache it, and retur
baselines/models_pytorch/mrc_pytorch/tools/file_utils.py:73
↓ 2 callersFunctioncalc_em_score
(answers, prediction)
baselines/models_pytorch/mrc_pytorch/preprocess/cmrc2018_evaluate.py:175
↓ 2 callersFunctioncalc_f1_score
(answers, prediction)
baselines/models_pytorch/mrc_pytorch/preprocess/cmrc2018_evaluate.py:159
↓ 2 callersFunctioncalc_global_pred_results
(logits)
baselines/paddlenlp/mrc/run_chid.py:156
↓ 2 callersFunctioncalculate_metrics
(correct, guessed, total)
baselines/models/roberta/conlleval.py:152
↓ 2 callersFunctioncalculate_metrics
(correct, guessed, total)
baselines/models/roberta_wwm_ext/conlleval.py:152
↓ 2 callersFunctioncalculate_metrics
(correct, guessed, total)
baselines/models/ernie/conlleval.py:152
↓ 2 callersFunctioncalculate_metrics
(correct, guessed, total)
baselines/models/bert_wwm_ext/conlleval.py:152
↓ 2 callersFunctioncalculate_metrics
(correct, guessed, total)
baselines/models/roberta_wwm_large_ext/conlleval.py:152
↓ 2 callersFunctioncalculate_metrics
(correct, guessed, total)
baselines/models/bert/conlleval.py:152
↓ 2 callersFunctioncompute_loss
(logits, positions)
baselines/models/roberta_wwm_ext/run_squad.py:646
↓ 2 callersFunctioncompute_loss
(logits, positions)
baselines/models/ernie/run_squad.py:646
↓ 2 callersFunctioncompute_loss
(logits, positions)
baselines/models/bert_wwm_ext/run_squad.py:646
↓ 2 callersFunctioncompute_loss
(logits, positions)
baselines/models/roberta_wwm_large_ext/run_squad.py:646
↓ 2 callersFunctioncompute_loss
(logits, positions)
baselines/models/bert/run_squad.py:646
↓ 2 callersFunctioncompute_loss
(log_probs, positions)
baselines/models/xlnet/run_cmrc_drcd.py:1052
↓ 2 callersMethodconvert
(self, string)
baselines/models_pytorch/mrc_pytorch/tools/langconv.py:216
↓ 2 callersFunctionconvert_examples_to_features
将所有候选答案放置在片段开头
baselines/models_pytorch/mrc_pytorch/preprocess/CHID_preprocess.py:217
↓ 2 callersFunctionconvert_examples_to_features
Loads a data file into a list of `InputBatch`s.
baselines/models/roberta_wwm_ext/run_squad.py:309
↓ 2 callersFunctionconvert_examples_to_features
Loads a data file into a list of `InputBatch`s.
baselines/models/ernie/run_squad.py:309
↓ 2 callersFunctionconvert_examples_to_features
Loads a data file into a list of `InputBatch`s.
baselines/models/bert_wwm_ext/run_squad.py:309
↓ 2 callersFunctionconvert_examples_to_features
Loads a data file into a list of `InputBatch`s.
baselines/models/roberta_wwm_large_ext/run_squad.py:309
↓ 2 callersFunctionconvert_examples_to_features
Loads a data file into a list of `InputBatch`s.
baselines/models/bert/run_squad.py:309
↓ 2 callersFunctionconvert_examples_to_features
Loads a data file into a list of `InputBatch`s.
baselines/models/xlnet/run_cmrc_drcd.py:317
↓ 2 callersMethodconvert_ids_to_tokens
Converts a single index or a sequence of indices (integers) in a token " (resp.) a sequence of tokens (str/unicode), using the vocabulary
baselines/models_pytorch/classifier_pytorch/transformers/tokenization_utils.py:958
↓ 2 callersFunctionconvert_single_example
Converts a single `InputExample` into a single `InputFeatures`.
baselines/models/roberta/run_classifier.py:309
↓ 2 callersFunctionconvert_single_example
(ex_index, example, label_list, max_seq_length, tokenizer, output_dir, mode)
baselines/models/roberta/run_ner.py:356
↓ 2 callersFunctionconvert_single_example
Converts a single `InputExample` into a single `InputFeatures`.
baselines/models/albert/run_classifier.py:305
↓ 2 callersFunctionconvert_single_example
Converts a single `InputExample` into a single `InputFeatures`.
baselines/models/roberta_wwm_ext/run_classifier.py:304
↓ 2 callersFunctionconvert_single_example
(ex_index, example, label_list, max_seq_length, tokenizer, output_dir, mode)
baselines/models/roberta_wwm_ext/run_ner.py:356
↓ 2 callersFunctionconvert_single_example
Converts a single `InputExample` into a single `InputFeatures`.
baselines/models/ernie/run_classifier.py:304
↓ 2 callersFunctionconvert_single_example
(ex_index, example, label_list, max_seq_length, tokenizer, output_dir, mode)
baselines/models/ernie/run_ner.py:356
↓ 2 callersFunctionconvert_single_example
Converts a single `InputExample` into a single `InputFeatures`.
baselines/models/bert_wwm_ext/run_classifier.py:304
↓ 2 callersFunctionconvert_single_example
(ex_index, example, label_list, max_seq_length, tokenizer, output_dir, mode)
baselines/models/bert_wwm_ext/run_ner.py:356
↓ 2 callersFunctionconvert_single_example
Converts a single `InputExample` into a single `InputFeatures`.
baselines/models/roberta_wwm_large_ext/run_classifier.py:307
↓ 2 callersFunctionconvert_single_example
(ex_index, example, label_list, max_seq_length, tokenizer, output_dir, mode)
baselines/models/roberta_wwm_large_ext/run_ner.py:356
↓ 2 callersFunctionconvert_single_example
Converts a single `InputExample` into a single `InputFeatures`.
baselines/models/bert/run_classifier.py:305
↓ 2 callersFunctionconvert_single_example
(ex_index, example, label_list, max_seq_length, tokenizer, output_dir, mode)
baselines/models/bert/run_ner.py:363
↓ 2 callersFunctionconvert_single_example_for_inews
(ex_index, tokens_a, tokens_b, label_map, max_seq_length, tokenizer, exam
baselines/models/roberta/run_classifier.py:154
↓ 2 callersFunctionconvert_single_example_for_inews
(ex_index, tokens_a, tokens_b, label_map, max_seq_length, tokenizer, exam
baselines/models/albert/run_classifier.py:150
↓ 2 callersFunctionconvert_single_example_for_inews
(ex_index, tokens_a, tokens_b, label_map, max_seq_length, tokenizer, exam
baselines/models/roberta_wwm_ext/run_classifier.py:149
↓ 2 callersFunctionconvert_single_example_for_inews
(ex_index, tokens_a, tokens_b, label_map, max_seq_length, tokenizer, exam
baselines/models/ernie/run_classifier.py:149
↓ 2 callersFunctionconvert_single_example_for_inews
(ex_index, tokens_a, tokens_b, label_map, max_seq_length, tokenizer, exam
baselines/models/bert_wwm_ext/run_classifier.py:149
↓ 2 callersFunctionconvert_single_example_for_inews
(ex_index, tokens_a, tokens_b, label_map, max_seq_length, tokenizer, exam
baselines/models/roberta_wwm_large_ext/run_classifier.py:152
↓ 2 callersFunctionconvert_single_example_for_inews
(ex_index, tokens_a, tokens_b, label_map, max_seq_length, tokenizer, exam
baselines/models/bert/run_classifier.py:150
↓ 2 callersFunctionconvert_single_example_for_inews
(ex_index, tokens_a, tokens_b, label_map, max_seq_length, tokenizer, exam
baselines/models/xlnet/run_classifier.py:289
↓ 2 callersFunctionconvert_tf_checkpoint_to_pytorch
(tf_checkpoint_path, bert_config_file, pytorch_dump_path)
baselines/models_pytorch/classifier_pytorch/convert_bert_original_tf_checkpoint_to_pytorch.py:15
↓ 2 callersMethodconvert_to_tensor
(self, symbols)
baselines/models_pytorch/classifier_pytorch/transformers/tokenization_transfo_xl.py:245
↓ 2 callersMethodconvert_tokens_to_string
Converts a sequence of tokens (string) in a single string. The most simple way to do it is ' '.join(self.convert_ids_to_tokens(token_ids)
baselines/models_pytorch/classifier_pytorch/transformers/tokenization_utils.py:983
↓ 2 callersFunctionconvert_xlnet_checkpoint_to_pytorch
(tf_checkpoint_path, bert_config_file, pytorch_dump_folder_path)
baselines/models_pytorch/classifier_pytorch/convert_xlnet_original_tf_checkpoint_to_pytorch.py:19
↓ 2 callersMethodcreate_cpu_hostcall
Runs on the host_call on CPU instead of TPU when use_tpu=False.
baselines/models/xlnet/tpu_estimator.py:1673
↓ 2 callersFunctioncreate_masked_lm_predictions
Creates the predictions for the masked LM objective.
baselines/models/roberta/create_pretraining_data.py:501
↓ 2 callersFunctioncreate_masked_lm_predictions
Creates the predictions for the masked LM objective.
baselines/models/albert/create_pretraining_data.py:498
↓ 2 callersFunctioncreate_masked_lm_predictions
Creates the predictions for the masked LM objective.
baselines/models/albert/resources/create_pretraining_data_roberta.py:501
↓ 2 callersFunctionembedding_lookup_factorized
Looks up words embeddings for id tensor, but in a factorized style followed by albert. it is used to reduce much percentage of parameters previous exi
baselines/models/albert/modeling.py:448
↓ 2 callersMethodencode_plus
Returns a dictionary containing the encoded sequence or sequence pair and additional informations: the mask for sequence classificati
baselines/models_pytorch/classifier_pytorch/transformers/tokenization_utils.py:739
↓ 2 callersFunctionend_of_chunk
(prev_tag, tag, prev_type, type_)
baselines/models/roberta/conlleval.py:233
↓ 2 callersFunctionend_of_chunk
(prev_tag, tag, prev_type, type_)
baselines/models/roberta_wwm_ext/conlleval.py:233
↓ 2 callersFunctionend_of_chunk
(prev_tag, tag, prev_type, type_)
baselines/models/ernie/conlleval.py:233
↓ 2 callersFunctionend_of_chunk
(prev_tag, tag, prev_type, type_)
baselines/models/bert_wwm_ext/conlleval.py:233
↓ 2 callersFunctionend_of_chunk
(prev_tag, tag, prev_type, type_)
baselines/models/roberta_wwm_large_ext/conlleval.py:233
↓ 2 callersFunctionend_of_chunk
(prev_tag, tag, prev_type, type_)
baselines/models/bert/conlleval.py:233
↓ 2 callersFunctionevaluate
(model, raw_dataset, dataset, data_loader, args, do_eval=True)
baselines/paddlenlp/mrc/run_cmrc2018.py:193
↓ 2 callersFunctionevaluate
(model, data_loader, do_predict=False)
baselines/paddlenlp/mrc/run_chid.py:180
↓ 2 callersFunctionevaluate
(args, model, tokenizer, prefix="")
baselines/models_pytorch/classifier_pytorch/run_classifier.py:160
↓ 2 callersFunctionfind_best_thresh
(preds, scores, na_probs, qid_to_has_ans)
baselines/models/xlnet/squad_utils.py:202
↓ 2 callersFunctionfind_best_thresh_v2
(preds, scores, na_probs, qid_to_has_ans)
baselines/models/xlnet/squad_utils.py:223
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