MCPcopy Create free account

hub / github.com/brightmart/slot_filling_intent_joint_model / functions

Functions417 in github.com/brightmart/slot_filling_intent_joint_model

⨍ Functions 417◇ Types & classes 11
↓ 2 callersFunctiongenerate_training_data
generate training data from a file, return training,validation and test set. traininig data contain x,y_intent,y_slots: x for sentence,y_intent
joint_model_knowl_v5_without_knowledge/a1_data_util.py:22
↓ 2 callersFunctiongenerate_training_data
generate training data from a file, return training,validation and test set. traininig data contain x,y_intent,y_slots: x for sentence,y_intent
joint_model_knowl_v7_with_domain_knowledge_context_window/a1_data_util.py:24
↓ 2 callersFunctiongenerate_training_data
generate training data from a file, return training,validation and test set. traininig data contain x,y_intent,y_slots: x for sentence,y_intent
joint_model_knowl_v3_bi_directional_cnn_tmall/a1_data_util.py:22
↓ 2 callersFunctiongenerate_training_data
generate training data from a file, return training,validation and test set. traininig data contain x,y_intent,y_slots: x for sentence,y_intent
joint_model_knowl_v8_slot_condition_intent/a1_data_util.py:24
↓ 2 callersFunctionget_attention_vector
get attention vector by concat context vector and current target hidden state, then use feed foward layer. attention_vector=tanh(Wc[c;h])
resources/a1_seq2seq.py:123
↓ 2 callersFunctionget_attention_vector
get attention vector by concat context vector and current target hidden state, then use feed foward layer. attention_vector=tanh(Wc[c;h])
joint_model_knowl_v0/a1_seq2seq.py:123
↓ 2 callersFunctionget_knowledge_list
(label_list,slots_voc_size,threshold=15)
resources/a1_joint_intent_slots_model.py:339
↓ 2 callersFunctionget_knowledge_list
(label_list,slots_voc_size,threshold=15)
joint_model_knowl_v2_simpl_modl_feat/joint_intent_slots_knowledge_model.py:276
↓ 2 callersFunctionget_knowledge_list
(label_list,slots_voc_size,threshold=15)
joint_model_knowl_v6_with_domain_knowledge/joint_intent_slots_knowledge_domain_model.py:413
↓ 2 callersFunctionget_knowledge_list
(label_list,slots_voc_size,threshold=15)
joint_model_knowl_v4_cnn_with_symbol_alime/joint_intent_slots_knowledge_model.py:390
↓ 2 callersFunctionget_knowledge_list
(label_list,slots_voc_size,threshold=15)
joint_model_knowl_v5_without_knowledge/joint_intent_slots_knowledge_model.py:390
↓ 2 callersFunctionget_knowledge_list
(label_list,slots_voc_size,threshold=15)
joint_model_knowl_v7_with_domain_knowledge_context_window/joint_intent_slots_knowledge_domain_model.py:407
↓ 2 callersFunctionget_knowledge_list
(label_list,slots_voc_size,threshold=15)
joint_model_knowl_v0/a1_joint_intent_slots_model.py:339
↓ 2 callersFunctionget_knowledge_list
(label_list,slots_voc_size,threshold=15)
joint_model_knowl_v3_bi_directional_cnn_tmall/joint_intent_slots_knowledge_model.py:383
↓ 2 callersFunctionget_knowledge_list
(label_list,slots_voc_size,threshold=15)
joint_model_naive_v1/joint_intent_slots_naive_model.py:263
↓ 2 callersFunctionget_target_from_list
(list, threshold=15)
resources/a1_joint_intent_slots_model.py:316
↓ 2 callersFunctionget_target_from_list
(list, threshold=15)
joint_model_knowl_v2_simpl_modl_feat/joint_intent_slots_knowledge_model.py:253
↓ 2 callersFunctionget_target_from_list
(list, threshold=15)
joint_model_knowl_v6_with_domain_knowledge/joint_intent_slots_knowledge_domain_model.py:390
↓ 2 callersFunctionget_target_from_list
(list, threshold=15)
joint_model_knowl_v4_cnn_with_symbol_alime/joint_intent_slots_knowledge_model.py:367
↓ 2 callersFunctionget_target_from_list
(list, threshold=15)
joint_model_knowl_v5_without_knowledge/joint_intent_slots_knowledge_model.py:367
↓ 2 callersFunctionget_target_from_list
(list, threshold=15)
joint_model_knowl_v7_with_domain_knowledge_context_window/joint_intent_slots_knowledge_domain_model.py:384
↓ 2 callersFunctionget_target_from_list
(list, threshold=15)
joint_model_knowl_v0/a1_joint_intent_slots_model.py:316
↓ 2 callersFunctionget_target_from_list
(list, threshold=15)
joint_model_knowl_v3_bi_directional_cnn_tmall/joint_intent_slots_knowledge_model.py:360
↓ 2 callersFunctionget_target_from_list
(list, threshold=15)
joint_model_naive_v1/joint_intent_slots_naive_model.py:240
↓ 2 callersFunctionget_unique_labels
(size)
resources/a1_joint_intent_slots_model.py:310
↓ 2 callersFunctionget_unique_labels
(size)
joint_model_knowl_v2_simpl_modl_feat/joint_intent_slots_knowledge_model.py:247
↓ 2 callersFunctionget_unique_labels
(size)
joint_model_knowl_v6_with_domain_knowledge/joint_intent_slots_knowledge_domain_model.py:384
↓ 2 callersFunctionget_unique_labels
(size)
joint_model_knowl_v4_cnn_with_symbol_alime/joint_intent_slots_knowledge_model.py:361
↓ 2 callersFunctionget_unique_labels
(size)
joint_model_knowl_v5_without_knowledge/joint_intent_slots_knowledge_model.py:361
↓ 2 callersFunctionget_unique_labels
(size)
joint_model_knowl_v7_with_domain_knowledge_context_window/joint_intent_slots_knowledge_domain_model.py:378
↓ 2 callersFunctionget_unique_labels
(size)
joint_model_knowl_v0/a1_joint_intent_slots_model.py:310
↓ 2 callersFunctionget_unique_labels
(size)
joint_model_knowl_v3_bi_directional_cnn_tmall/joint_intent_slots_knowledge_model.py:354
↓ 2 callersFunctionget_unique_labels
(size)
joint_model_naive_v1/joint_intent_slots_naive_model.py:234
↓ 2 callersMethodinference_intent
(self,inputs_concat)
joint_model_knowl_v9_intent_rank/joint_intent_slots_knowledge_rank_model.py:127
↓ 2 callersMethodinference_slot
(self,intent_hidden_states)
joint_model_knowl_v9_intent_rank/joint_intent_slots_knowledge_rank_model.py:135
↓ 2 callersFunctionloop_function
(prev, _)
resources/a1_seq2seq.py:13
↓ 2 callersFunctionloop_function
(prev, _)
joint_model_knowl_v0/a1_seq2seq.py:13
↓ 2 callersFunctionpredict
:param sentence: a sentence. :return: intent and slots
joint_model_knowl_v2_simpl_modl_feat/joint_intent_slots_knowledge_predict.py:82
↓ 2 callersFunctionpredict
:param sentence: a sentence. :return: intent and slots
joint_model_naive_v1/joint_intent_slots_navie_predict.py:69
↓ 1 callersFunctionaccuarcy_for_similiarity_validation_set
()
joint_model_knowl_v4_cnn_with_symbol_alime/joint_intent_slots_knowledge_predict.py:92
↓ 1 callersFunctionaccuarcy_for_similiarity_validation_set
()
joint_model_knowl_v5_without_knowledge/joint_intent_slots_knowledge_predict.py:92
↓ 1 callersFunctionaccuarcy_for_similiarity_validation_set
()
joint_model_knowl_v3_bi_directional_cnn_tmall/joint_intent_slots_knowledge_predict.py:92
↓ 1 callersFunctionassign_pretrained_word_embedding
assign pretrained word embedding to parameter of the model. :param sess: :param vocabulary_index2word: a dict of vocabulary of source sid
joint_model_knowl_v0/a1_joint_intent_slots_train.py:138
↓ 1 callersFunctioncompute_score_noise
compute whether it is a noise or not.今天 :param domain_score: :param intent_logits: :param slots: :return:
joint_model_knowl_v8_slot_condition_intent/joint_intent_slots_knowledge_conditional_predict.py:266
↓ 1 callersMethodconv_layer
(self)
joint_model_knowl_v4_cnn_with_symbol_alime/joint_intent_slots_knowledge_model.py:182
↓ 1 callersMethodconv_layer
(self)
joint_model_knowl_v5_without_knowledge/joint_intent_slots_knowledge_model.py:182
↓ 1 callersMethodconv_layer
(self)
joint_model_knowl_v3_bi_directional_cnn_tmall/joint_intent_slots_knowledge_model.py:175
↓ 1 callersFunctiondo_eval
(sess, model, evalX, evalY_input,evalY_output, batch_size)
joint_model_knowl_v0/a1_joint_intent_slots_train.py:184
↓ 1 callersMethodencoder
1.Word embedding. 2.Encoder with GRU
resources/a1_joint_intent_slots_model.py:71
↓ 1 callersMethodencoder
1.Word embedding. 2.Encoder with GRU
joint_model_knowl_v2_simpl_modl_feat/joint_intent_slots_knowledge_model.py:62
↓ 1 callersMethodencoder
1.Word embedding. 2.Encoder with GRU
joint_model_knowl_v6_with_domain_knowledge/joint_intent_slots_knowledge_domain_model.py:103
↓ 1 callersMethodencoder
1.Word embedding. 2.Encoder with GRU
joint_model_knowl_v4_cnn_with_symbol_alime/joint_intent_slots_knowledge_model.py:96
↓ 1 callersMethodencoder
1.Word embedding. 2.Encoder with GRU
joint_model_knowl_v5_without_knowledge/joint_intent_slots_knowledge_model.py:96
↓ 1 callersMethodencoder
1.Word embedding. 2.Encoder with GRU
joint_model_knowl_v0/a1_joint_intent_slots_model.py:71
↓ 1 callersMethodencoder
1.Word embedding. 2.Encoder with GRU
joint_model_knowl_v3_bi_directional_cnn_tmall/joint_intent_slots_knowledge_model.py:87
↓ 1 callersMethodencoder
1.Word embedding. 2.Encoder with GRU
joint_model_naive_v1/joint_intent_slots_naive_model.py:61
↓ 1 callersMethodencoder_bi_directional_alime
1.word vector+symbol vector 2.context window 3.nolinear projection 4.bi-directional lstm
joint_model_knowl_v9_intent_rank/joint_intent_slots_knowledge_rank_model.py:87
↓ 1 callersMethodencoder_bi_directional_alime
1.word vector+symbol vector 2.context window 3.nolinear projection 4.bi-directional lstm
joint_model_knowl_v7_with_domain_knowledge_context_window/joint_intent_slots_knowledge_domain_model.py:79
↓ 1 callersMethodencoder_bi_directional_alime
1.word vector+symbol vector 2.context window 3.nolinear projection 4.bi-directional lstm
joint_model_knowl_v8_slot_condition_intent/joint_intent_slots_knowledge_conditional_model.py:89
↓ 1 callersFunctionextract_argmax_and_embed
Get a loop_function that extracts the previous symbol and embeds it. Used by decoder. :param embedding: embedding tensor for symbol :para
resources/a1_seq2seq.py:5
↓ 1 callersFunctionextract_argmax_and_embed
Get a loop_function that extracts the previous symbol and embeds it. Used by decoder. :param embedding: embedding tensor for symbol :para
joint_model_knowl_v0/a1_seq2seq.py:5
↓ 1 callersFunctiongenerate_raw_data
(source_file_name,test_mode=False,knowledge_path=None,target_file=None)
joint_model_knowl_v2_simpl_modl_feat/a1_data_util.py:85
↓ 1 callersFunctiongenerate_raw_data_singel
(sline)
resources/a1_generate_raw_data_single.py:4
↓ 1 callersFunctiongenerate_raw_data_singel
(sline)
joint_model_knowl_v2_simpl_modl_feat/a1_data_util.py:112
↓ 1 callersFunctiongenerate_raw_data_singel
(sline)
joint_model_knowl_v6_with_domain_knowledge/a1_data_util.py:131
↓ 1 callersFunctiongenerate_raw_data_singel
(sline)
joint_model_knowl_v4_cnn_with_symbol_alime/a1_data_util.py:112
↓ 1 callersFunctiongenerate_raw_data_singel
(sline)
joint_model_knowl_v5_without_knowledge/a1_data_util.py:112
↓ 1 callersFunctiongenerate_raw_data_singel
(sline)
joint_model_knowl_v7_with_domain_knowledge_context_window/a1_data_util.py:131
↓ 1 callersFunctiongenerate_raw_data_singel
(sline)
joint_model_knowl_v0/a1_data_util.py:112
↓ 1 callersFunctiongenerate_raw_data_singel
(sline)
joint_model_knowl_v3_bi_directional_cnn_tmall/a1_data_util.py:112
↓ 1 callersFunctiongenerate_raw_data_singel
(sline)
joint_model_knowl_v8_slot_condition_intent/a1_data_util.py:140
↓ 1 callersFunctiongenerate_training_data
generate training data from a file, return training,validation and test set. traininig data contain x,y_intent,y_slots: x for sentence,y_intent
joint_model_knowl_v2_simpl_modl_feat/a1_data_util.py:22
↓ 1 callersFunctiongenerate_training_data
generate training data from a file, return training,validation and test set. traininig data contain x,y_intent,y_slots: x for sentence,y_intent
joint_model_knowl_v0/a1_data_util.py:22
↓ 1 callersFunctionget_attention_vector_simple
get attention vector by concat context vector and current target hidden state, then use feed foward layer. attention_vector=tanh(Wc[c;h])
resources/a1_seq2seq.py:106
↓ 1 callersFunctionget_attention_vector_simple
get attention vector by concat context vector and current target hidden state, then use feed foward layer. attention_vector=tanh(Wc[c;h])
joint_model_knowl_v0/a1_seq2seq.py:106
↓ 1 callersFunctionget_domain_and_real_intent
get domain information from dialog_template_id.e.g. dialog_template_id:'医疗问诊__问诊_疾病概述__2c9081a4602b882801602b8b468d0055' :param dialog_templa
joint_model_knowl_v6_with_domain_knowledge/a1_data_util.py:166
↓ 1 callersFunctionget_domain_and_real_intent
get domain information from dialog_template_id.e.g. dialog_template_id:'医疗问诊__问诊_疾病概述__2c9081a4602b882801602b8b468d0055' :param dialog_templa
joint_model_knowl_v7_with_domain_knowledge_context_window/a1_data_util.py:166
↓ 1 callersFunctionget_domain_and_real_intent
get domain information from dialog_template_id.e.g. dialog_template_id:'医疗问诊__问诊_疾病概述__2c9081a4602b882801602b8b468d0055' :param dialog_templa
joint_model_knowl_v8_slot_condition_intent/a1_data_util.py:186
↓ 1 callersFunctionget_knowledge
(data_source_file,knowledge_path,test_mode=False)
joint_model_knowl_v7_with_domain_knowledge_context_window/a1_generate_knowledges.py:14
↓ 1 callersFunctionget_knowledge
(data_source_file,knowledge_path,test_mode=False)
joint_model_knowl_v8_slot_condition_intent/a1_generate_knowledges.py:14
↓ 1 callersFunctionget_label_using_logits
:param predictions: array as [batch_size,decoder_sent_length] :param vocab_cn_index2word: :param vocab_cn: :return:
joint_model_knowl_v0/a1_joint_intent_slots_predict.py:86
↓ 1 callersFunctionget_result
(logits_intent,logits_slots,sentence_indices)
joint_model_knowl_v2_simpl_modl_feat/joint_intent_slots_knowledge_predict.py:143
↓ 1 callersFunctionget_result
(logits_intent,logits_slots,sentence_indices,similiarity_list,logits_domain,top_number=3)
joint_model_knowl_v6_with_domain_knowledge/joint_intent_slots_knowledge_domain_predict.py:234
↓ 1 callersFunctionget_result
(logits_intent,logits_slots,sentence_indices,similiarity_list,top_number=3)
joint_model_knowl_v4_cnn_with_symbol_alime/joint_intent_slots_knowledge_predict.py:225
↓ 1 callersFunctionget_result
(logits_intent,logits_slots,sentence_indices,similiarity_list,top_number=3)
joint_model_knowl_v5_without_knowledge/joint_intent_slots_knowledge_predict.py:225
↓ 1 callersFunctionget_result
(logits_intent,logits_slots,sentence_indices,similiarity_list,logits_domain,top_number=3)
joint_model_knowl_v7_with_domain_knowledge_context_window/joint_intent_slots_knowledge_domain_predict.py:233
↓ 1 callersFunctionget_result
(logits_intent,logits_slots,sentence_indices,similiarity_list,top_number=3)
joint_model_knowl_v3_bi_directional_cnn_tmall/joint_intent_slots_knowledge_predict.py:225
↓ 1 callersFunctionget_result
(logits_intent,logits_slots,sentence_indices,similiarity_list,logits_domain,top_number=3)
joint_model_knowl_v8_slot_condition_intent/joint_intent_slots_knowledge_conditional_predict.py:285
↓ 1 callersFunctionget_result
(logits_intent,logits_slots,sentence_indices)
joint_model_naive_v1/joint_intent_slots_navie_predict.py:98
↓ 1 callersFunctionget_sentence_from_index
(x_indices)
joint_model_knowl_v6_with_domain_knowledge/joint_intent_slots_knowledge_domain_predict.py:156
↓ 1 callersFunctionget_sentence_from_index
(x_indices)
joint_model_knowl_v4_cnn_with_symbol_alime/joint_intent_slots_knowledge_predict.py:149
↓ 1 callersFunctionget_sentence_from_index
(x_indices)
joint_model_knowl_v5_without_knowledge/joint_intent_slots_knowledge_predict.py:149
↓ 1 callersFunctionget_sentence_from_index
(x_indices)
joint_model_knowl_v7_with_domain_knowledge_context_window/joint_intent_slots_knowledge_domain_predict.py:156
↓ 1 callersFunctionget_sentence_from_index
(x_indices)
joint_model_knowl_v3_bi_directional_cnn_tmall/joint_intent_slots_knowledge_predict.py:149
↓ 1 callersFunctionget_sentence_from_index
(x_indices)
joint_model_knowl_v8_slot_condition_intent/joint_intent_slots_knowledge_conditional_predict.py:193
↓ 1 callersFunctionget_training_valid_test_data
generate training,validation and test data. :param data_dict: :param word2id_x: :param sequence_length: :param word2id_intent:
joint_model_knowl_v2_simpl_modl_feat/a1_data_util.py:146
↓ 1 callersFunctionget_training_valid_test_data
generate training,validation and test data. :param data_dict: :param word2id_x: :param sequence_length: :param word2id_intent:
joint_model_knowl_v6_with_domain_knowledge/a1_data_util.py:189
↓ 1 callersFunctionget_training_valid_test_data
generate training,validation and test data. :param data_dict: :param word2id_x: :param sequence_length: :param word2id_intent:
joint_model_knowl_v4_cnn_with_symbol_alime/a1_data_util.py:146
↓ 1 callersFunctionget_training_valid_test_data
generate training,validation and test data. :param data_dict: :param word2id_x: :param sequence_length: :param word2id_intent:
joint_model_knowl_v5_without_knowledge/a1_data_util.py:146
↓ 1 callersFunctionget_training_valid_test_data
generate training,validation and test data. :param data_dict: :param word2id_x: :param sequence_length: :param word2id_intent:
joint_model_knowl_v7_with_domain_knowledge_context_window/a1_data_util.py:189
← previousnext →101–200 of 417, ranked by callers