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Functions157 in github.com/HIT-SCIR/plm-nlp-code

⨍ Functions 157◇ Types & classes 37

↓ 8 callersMethodconvert_tokens_to_ids

chp4/vocab.py:35

↓ 6 callersFunctionget_loader

(dataset, batch_size, shuffle=True)

chp5/utils.py:52

↓ 6 callersFunctionload_reuters

chp5/utils.py:14

↓ 6 callersFunctionsave_pretrained

Save pretrained token vectors in a unified format, where the first line specifies the `number_of_tokens` and `embedding_dim` followed with al

chp5/utils.py:24

↓ 4 callersMethod__init__

(self, configs, vocab_w, vocab_c)

chp6/train_elmo.py:283

↓ 4 callersFunctionload_sentence_polarity

chp4/utils.py:6

↓ 3 callersMethodbuild

(cls, text, min_freq=1, reserved_tokens=None)

chp4/vocab.py:19

↓ 3 callersMethodconvert_tokens_to_ids

chp6/vocab.py:35

↓ 3 callersFunctioninit_weights

chp5/utils.py:61

↓ 2 callersMethodbuild

(cls, text, min_freq=1, reserved_tokens=None)

chp6/vocab.py:19

↓ 2 callersMethodconvert_ids_to_tokens

(self, indices)

chp5/vocab.py:38

↓ 2 callersMethodconvert_tokens_to_ids

chp5/vocab.py:35

↓ 2 callersMethodforward_c

(self, contexts)

chp5/sgns.py:66

↓ 2 callersFunctionknn

chp5/evaluate.py:6

↓ 2 callersFunctionlength_to_mask

chp4/utils.py:23

↓ 2 callersFunctionload_pretrained

chp5/utils.py:37

↓ 2 callersFunctionload_treebank

chp4/utils.py:28

↓ 2 callersFunctionsave_vocab

chp6/vocab.py:42

↓ 1 callersMethod__init__

(self, vocab_size, embedding_dim, hidden_dim, num_class, dim_feedforward=512, num_head=2, num

chp4/transformer_sent_polarity.py:49

↓ 1 callersMethod__init__

(self, vocab_size, embedding_dim, hidden_dim, num_class, dim_feedforward=512, num_head=2, num

chp4/transformer_postag.py:52

↓ 1 callersMethod__init__

(self, corpus, vocab, context_size=2)

chp5/ffnnlm.py:13

↓ 1 callersMethodbuild

(cls, text, min_freq=1, reserved_tokens=None)

chp5/vocab.py:19

↓ 1 callersFunctionfind_analogy

(embeds, vocab, word_a, word_b, word_c)

chp5/evaluate.py:24

↓ 1 callersFunctionfind_similar_words

(embeds, vocab, query, k=5)

chp5/evaluate.py:11

↓ 1 callersFunctionfmm_word_seg

(sentence, lexicon, max_len)

chp2/fmm_word_seg.py:16

↓ 1 callersMethodforward_c

(self, contexts)

chp5/glove.py:60

↓ 1 callersMethodforward_w

chp5/sgns.py:62

↓ 1 callersMethodforward_w

chp5/glove.py:55

↓ 1 callersFunctionget_loader

(dataset, batch_size, shuffle=True)

chp6/utils.py:52

↓ 1 callersFunctionget_unigram_distribution

(corpus, vocab_size)

chp5/sgns.py:71

↓ 1 callersFunctioninit_weights

chp4/lstm_postag.py:36

↓ 1 callersFunctionload_corpus

(path, max_tok_len=None, max_seq_len=None)

chp6/train_elmo.py:21

↓ 1 callersFunctionload_dict

chp2/fmm_word_seg.py:3

↓ 1 callersFunctionpmi

(M, positive=True)

↓ 1 callersFunctionremove_control_chars

chp3/wikidata_cleaning.py:13

↓ 1 callersFunctionremove_empty_paired_punc

chp3/wikidata_cleaning.py:6

↓ 1 callersFunctionremove_html_tags

chp3/wikidata_cleaning.py:9

↓ 1 callersMethodsave_pretrained

chp6/train_elmo.py:311

Method__getitem__

chp4/transformer_sent_polarity.py:21

Method__getitem__

chp4/lstm_postag.py:24

Method__getitem__

chp4/transformer_postag.py:21

Method__getitem__

chp4/cnn_sent_polarity.py:17

Method__getitem__

chp4/mlp_sent_polarity.py:16

Method__getitem__

chp4/vocab.py:32

Method__getitem__

chp4/lstm_sent_polarity.py:20

Method__getitem__

chp5/sgns.py:38

Method__getitem__

chp5/rnnlm.py:29

Method__getitem__

chp5/skipgram.py:32

Method__getitem__

chp5/vocab.py:32

Method__getitem__

chp5/ffnnlm.py:32

Method__getitem__

chp5/cbow.py:32

Method__getitem__

chp5/glove.py:36

Method__getitem__

chp6/train_elmo.py:85

Method__getitem__

chp6/vocab.py:32

chp4/transformer_sent_polarity.py:17

(self, d_model, dropout=0.1, max_len=512)

chp4/transformer_sent_polarity.py:33

chp4/lstm_postag.py:18

(self, vocab_size, embedding_dim, hidden_dim, num_class)

chp4/lstm_postag.py:41

chp4/transformer_postag.py:17

(self, d_model, dropout=0.1, max_len=512)

chp4/transformer_postag.py:34

(self, input_dim, hidden_dim, num_class)

chp4/mlp_train.py:6

chp4/cnn_sent_polarity.py:13

(self, vocab_size, embedding_dim, filter_size, num_filter, num_class)

chp4/cnn_sent_polarity.py:28

(self, vocab_size, embedding_dim, hidden_dim, num_class)

chp4/mlp_embedding.py:6

chp4/mlp_sent_polarity.py:12

(self, vocab_size, embedding_dim, hidden_dim, num_class)

chp4/mlp_sent_polarity.py:28

(self, input_dim, hidden_dim, num_class)

(self, tokens=None)

chp4/vocab.py:6

chp4/lstm_sent_polarity.py:16

(self, vocab_size, embedding_dim, hidden_dim, num_class)

chp4/lstm_sent_polarity.py:32

(self, corpus, vocab, context_size=2, n_negatives=5, ns_dist=None)

chp5/sgns.py:14

(self, vocab_size, embedding_dim)

chp5/sgns.py:55

(self, corpus, vocab)

chp5/rnnlm.py:14

(self, vocab_size, embedding_dim, hidden_dim)

chp5/rnnlm.py:42

(self, corpus, vocab, context_size=2)

chp5/skipgram.py:14

(self, vocab_size, embedding_dim)

chp5/skipgram.py:41

(self, tokens=None)

chp5/vocab.py:6

(self, vocab_size, embedding_dim, context_size, hidden_dim)

chp5/ffnnlm.py:42

(self, corpus, vocab, context_size=2)

chp5/cbow.py:14

(self, vocab_size, embedding_dim)

chp5/cbow.py:41

(self, corpus, vocab, context_size=2)

chp5/glove.py:15

(self, vocab_size, embedding_dim)

chp5/glove.py:46

(self, corpus_w, corpus_c, vocab_w, vocab_c)

chp6/train_elmo.py:73

(self, input_dim, num_layers, activation=F.relu)

chp6/train_elmo.py:116

( self, vocab_c, char_embedding_dim, char_conv_filters, num_highways,

chp6/train_elmo.py:139

( self, input_dim, hidden_dim, num_layers, dropout_prob=0.0 )

chp6/train_elmo.py:195

(self, tokens=None)

chp6/vocab.py:6

chp4/transformer_sent_polarity.py:19

chp4/lstm_postag.py:21

chp4/transformer_postag.py:19

chp4/cnn_sent_polarity.py:15

chp4/mlp_sent_polarity.py:14

chp4/vocab.py:29

chp4/lstm_sent_polarity.py:18

chp5/sgns.py:35

chp5/rnnlm.py:26

chp5/skipgram.py:29

chp5/vocab.py:29

chp5/ffnnlm.py:29

chp5/cbow.py:29

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