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Functions417 in github.com/brightmart/slot_filling_intent_joint_model

⨍ Functions 417◇ Types & classes 11
↓ 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_v0/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_v3_bi_directional_cnn_tmall/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_v8_slot_condition_intent/a1_data_util.py:209
↓ 1 callersFunctionget_y_slots
get y_slots using dictt.e.g. dictt={'slots': {'全部范围': '全', '房间': '储藏室', '设备名': '四开开关'}, 'user': '替我把储藏室四开开关全关闭一下', 'intent': '关设备<房间><全部范围><设备名>'}
joint_model_knowl_v2_simpl_modl_feat/a1_data_util.py:350
↓ 1 callersFunctionget_y_slots
get y_slots using dictt.e.g. dictt={'slots': {'全部范围': '全', '房间': '储藏室', '设备名': '四开开关'}, 'user': '替我把储藏室四开开关全关闭一下', 'intent': '关设备<房间><全部范围><设备名>'}
joint_model_knowl_v6_with_domain_knowledge/a1_data_util.py:435
↓ 1 callersFunctionget_y_slots
get y_slots using dictt.e.g. dictt={'slots': {'全部范围': '全', '房间': '储藏室', '设备名': '四开开关'}, 'user': '替我把储藏室四开开关全关闭一下', 'intent': '关设备<房间><全部范围><设备名>'}
joint_model_knowl_v4_cnn_with_symbol_alime/a1_data_util.py:350
↓ 1 callersFunctionget_y_slots
get y_slots using dictt.e.g. dictt={'slots': {'全部范围': '全', '房间': '储藏室', '设备名': '四开开关'}, 'user': '替我把储藏室四开开关全关闭一下', 'intent': '关设备<房间><全部范围><设备名>'}
joint_model_knowl_v5_without_knowledge/a1_data_util.py:350
↓ 1 callersFunctionget_y_slots
get y_slots using dictt.e.g. dictt={'slots': {'全部范围': '全', '房间': '储藏室', '设备名': '四开开关'}, 'user': '替我把储藏室四开开关全关闭一下', 'intent': '关设备<房间><全部范围><设备名>'}
joint_model_knowl_v7_with_domain_knowledge_context_window/a1_data_util.py:435
↓ 1 callersFunctionget_y_slots
get y_slots using dictt.e.g. dictt={'slots': {'全部范围': '全', '房间': '储藏室', '设备名': '四开开关'}, 'user': '替我把储藏室四开开关全关闭一下', 'intent': '关设备<房间><全部范围><设备名>'}
joint_model_knowl_v0/a1_data_util.py:350
↓ 1 callersFunctionget_y_slots
get y_slots using dictt.e.g. dictt={'slots': {'全部范围': '全', '房间': '储藏室', '设备名': '四开开关'}, 'user': '替我把储藏室四开开关全关闭一下', 'intent': '关设备<房间><全部范围><设备名>'}
joint_model_knowl_v3_bi_directional_cnn_tmall/a1_data_util.py:350
↓ 1 callersFunctionget_y_slots
get y_slots using dictt.e.g. dictt={'slots': {'全部范围': '全', '房间': '储藏室', '设备名': '四开开关'}, 'user': '替我把储藏室四开开关全关闭一下', 'intent': '关设备<房间><全部范围><设备名>'}
joint_model_knowl_v8_slot_condition_intent/a1_data_util.py:455
↓ 1 callersFunctionget_y_slots_by_knowledge
get y_slots using dictt.e.g. dictt={'slots': {'全部范围': '全', '房间': '储藏室', '设备名': '四开开关'}, 'user': '替我把储藏室四开开关全关闭一下', 'intent': '关设备<房间><全部范围><设备名>'}
joint_model_knowl_v2_simpl_modl_feat/joint_intent_slots_knowledge_predict.py:96
↓ 1 callersFunctionget_y_slots_by_knowledge
get y_slots using dictt.e.g. dictt={'slots': {'全部范围': '全', '房间': '储藏室', '设备名': '四开开关'}, 'user': '替我把储藏室四开开关全关闭一下', 'intent': '关设备<房间><全部范围><设备名>'}
joint_model_knowl_v6_with_domain_knowledge/joint_intent_slots_knowledge_domain_predict.py:180
↓ 1 callersFunctionget_y_slots_by_knowledge
get y_slots using dictt.e.g. dictt={'slots': {'全部范围': '全', '房间': '储藏室', '设备名': '四开开关'}, 'user': '替我把储藏室四开开关全关闭一下', 'intent': '关设备<房间><全部范围><设备名>'}
joint_model_knowl_v4_cnn_with_symbol_alime/joint_intent_slots_knowledge_predict.py:172
↓ 1 callersFunctionget_y_slots_by_knowledge
get y_slots using dictt.e.g. dictt={'slots': {'全部范围': '全', '房间': '储藏室', '设备名': '四开开关'}, 'user': '替我把储藏室四开开关全关闭一下', 'intent': '关设备<房间><全部范围><设备名>'}
joint_model_knowl_v5_without_knowledge/joint_intent_slots_knowledge_predict.py:172
↓ 1 callersFunctionget_y_slots_by_knowledge
get y_slots using dictt.e.g. dictt={'slots': {'全部范围': '全', '房间': '储藏室', '设备名': '四开开关'}, 'user': '替我把储藏室四开开关全关闭一下', 'intent': '关设备<房间><全部范围><设备名>'}
joint_model_knowl_v7_with_domain_knowledge_context_window/joint_intent_slots_knowledge_domain_predict.py:179
↓ 1 callersFunctionget_y_slots_by_knowledge
get y_slots using dictt.e.g. dictt={'slots': {'全部范围': '全', '房间': '储藏室', '设备名': '四开开关'}, 'user': '替我把储藏室四开开关全关闭一下', 'intent': '关设备<房间><全部范围><设备名>'}
joint_model_knowl_v3_bi_directional_cnn_tmall/joint_intent_slots_knowledge_predict.py:172
↓ 1 callersFunctionget_y_slots_by_knowledge
get y_slots using dictt.e.g. dictt={'slots': {'全部范围': '全', '房间': '储藏室', '设备名': '四开开关'}, 'user': '替我把储藏室四开开关全关闭一下', 'intent': '关设备<房间><全部范围><设备名>'}
joint_model_knowl_v8_slot_condition_intent/joint_intent_slots_knowledge_conditional_predict.py:216
↓ 1 callersMethodinference_domain
(self)
joint_model_knowl_v9_intent_rank/joint_intent_slots_knowledge_rank_model.py:120
↓ 1 callersMethodinference_domain
(self)
joint_model_knowl_v6_with_domain_knowledge/joint_intent_slots_knowledge_domain_model.py:120
↓ 1 callersMethodinference_domain
(self)
joint_model_knowl_v7_with_domain_knowledge_context_window/joint_intent_slots_knowledge_domain_model.py:112
↓ 1 callersMethodinference_domain
(self)
joint_model_knowl_v8_slot_condition_intent/joint_intent_slots_knowledge_conditional_model.py:122
↓ 1 callersMethodinference_intent
main computation graph here: 1.embedding-->2.convolution-pooling layer(a.create filters,b.conv,c.apply nolinearity,d.max-pooling)-->3.concat--->linear
resources/a1_joint_intent_slots_model.py:112
↓ 1 callersMethodinference_intent
(self)
joint_model_knowl_v2_simpl_modl_feat/joint_intent_slots_knowledge_model.py:77
↓ 1 callersMethodinference_intent
(self)
joint_model_knowl_v6_with_domain_knowledge/joint_intent_slots_knowledge_domain_model.py:114
↓ 1 callersMethodinference_intent
(self)
joint_model_knowl_v4_cnn_with_symbol_alime/joint_intent_slots_knowledge_model.py:107
↓ 1 callersMethodinference_intent
(self)
joint_model_knowl_v5_without_knowledge/joint_intent_slots_knowledge_model.py:107
↓ 1 callersMethodinference_intent
(self)
joint_model_knowl_v7_with_domain_knowledge_context_window/joint_intent_slots_knowledge_domain_model.py:118
↓ 1 callersMethodinference_intent
main computation graph here: 1.embedding-->2.convolution-pooling layer(a.create filters,b.conv,c.apply nolinearity,d.max-pooling)-->3.concat--->linear
joint_model_knowl_v0/a1_joint_intent_slots_model.py:112
↓ 1 callersMethodinference_intent
(self)
joint_model_knowl_v3_bi_directional_cnn_tmall/joint_intent_slots_knowledge_model.py:97
↓ 1 callersMethodinference_intent
(self)
joint_model_knowl_v8_slot_condition_intent/joint_intent_slots_knowledge_conditional_model.py:129
↓ 1 callersMethodinference_intent
(self)
joint_model_naive_v1/joint_intent_slots_naive_model.py:74
↓ 1 callersMethodinference_slot
main computation graph here: 1.prepare decode parameters; 2.decode with attention 3.dropout 4.get logits.
resources/a1_joint_intent_slots_model.py:85
↓ 1 callersMethodinference_slot
(self)
joint_model_knowl_v2_simpl_modl_feat/joint_intent_slots_knowledge_model.py:91
↓ 1 callersMethodinference_slot
(self)
joint_model_knowl_v6_with_domain_knowledge/joint_intent_slots_knowledge_domain_model.py:127
↓ 1 callersMethodinference_slot
(self)
joint_model_knowl_v4_cnn_with_symbol_alime/joint_intent_slots_knowledge_model.py:114
↓ 1 callersMethodinference_slot
(self)
joint_model_knowl_v5_without_knowledge/joint_intent_slots_knowledge_model.py:114
↓ 1 callersMethodinference_slot
(self)
joint_model_knowl_v7_with_domain_knowledge_context_window/joint_intent_slots_knowledge_domain_model.py:124
↓ 1 callersMethodinference_slot
main computation graph here: 1.prepare decode parameters; 2.decode with attention 3.dropout 4.get logits.
joint_model_knowl_v0/a1_joint_intent_slots_model.py:85
↓ 1 callersMethodinference_slot
(self)
joint_model_knowl_v3_bi_directional_cnn_tmall/joint_intent_slots_knowledge_model.py:118
↓ 1 callersMethodinference_slot
(self)
joint_model_knowl_v8_slot_condition_intent/joint_intent_slots_knowledge_conditional_model.py:138
↓ 1 callersMethodinference_slot
(self)
joint_model_naive_v1/joint_intent_slots_naive_model.py:86
↓ 1 callersMethodinstantiate_weights
define all weights here
resources/a1_joint_intent_slots_model.py:194
↓ 1 callersMethodinstantiate_weights
define all weights here
joint_model_knowl_v9_intent_rank/joint_intent_slots_knowledge_rank_model.py:279
↓ 1 callersMethodinstantiate_weights
define all weights here
joint_model_knowl_v2_simpl_modl_feat/joint_intent_slots_knowledge_model.py:137
↓ 1 callersMethodinstantiate_weights
define all weights here
joint_model_knowl_v6_with_domain_knowledge/joint_intent_slots_knowledge_domain_model.py:269
↓ 1 callersMethodinstantiate_weights
define all weights here
joint_model_knowl_v4_cnn_with_symbol_alime/joint_intent_slots_knowledge_model.py:251
↓ 1 callersMethodinstantiate_weights
define all weights here
joint_model_knowl_v5_without_knowledge/joint_intent_slots_knowledge_model.py:251
↓ 1 callersMethodinstantiate_weights
define all weights here
joint_model_knowl_v7_with_domain_knowledge_context_window/joint_intent_slots_knowledge_domain_model.py:263
↓ 1 callersMethodinstantiate_weights
define all weights here
joint_model_knowl_v0/a1_joint_intent_slots_model.py:194
↓ 1 callersMethodinstantiate_weights
define all weights here
joint_model_knowl_v3_bi_directional_cnn_tmall/joint_intent_slots_knowledge_model.py:244
↓ 1 callersMethodinstantiate_weights
define all weights here
joint_model_knowl_v8_slot_condition_intent/joint_intent_slots_knowledge_conditional_model.py:277
↓ 1 callersMethodinstantiate_weights
define all weights here
joint_model_naive_v1/joint_intent_slots_naive_model.py:124
↓ 1 callersFunctionload_knowledge
(knowledge_path)
joint_model_knowl_v2_simpl_modl_feat/a1_data_util.py:336
↓ 1 callersFunctionload_knowledge
(knowledge_path)
joint_model_knowl_v6_with_domain_knowledge/a1_data_util.py:420
↓ 1 callersFunctionload_knowledge
(knowledge_path)
joint_model_knowl_v4_cnn_with_symbol_alime/a1_data_util.py:336
↓ 1 callersFunctionload_knowledge
(knowledge_path)
joint_model_knowl_v5_without_knowledge/a1_data_util.py:336
↓ 1 callersFunctionload_knowledge
(knowledge_path)
joint_model_knowl_v7_with_domain_knowledge_context_window/a1_data_util.py:420
↓ 1 callersFunctionload_knowledge
(knowledge_path)
joint_model_knowl_v3_bi_directional_cnn_tmall/a1_data_util.py:336
↓ 1 callersFunctionload_knowledge
(knowledge_path)
joint_model_knowl_v8_slot_condition_intent/a1_data_util.py:440
↓ 1 callersMethodloss_seq2seq
(self)
resources/a1_joint_intent_slots_model.py:169
↓ 1 callersMethodloss_seq2seq
(self)
joint_model_knowl_v9_intent_rank/joint_intent_slots_knowledge_rank_model.py:238
↓ 1 callersMethodloss_seq2seq
(self)
joint_model_knowl_v2_simpl_modl_feat/joint_intent_slots_knowledge_model.py:107
↓ 1 callersMethodloss_seq2seq
(self)
joint_model_knowl_v6_with_domain_knowledge/joint_intent_slots_knowledge_domain_model.py:234
↓ 1 callersMethodloss_seq2seq
(self)
joint_model_knowl_v4_cnn_with_symbol_alime/joint_intent_slots_knowledge_model.py:221
↓ 1 callersMethodloss_seq2seq
(self)
joint_model_knowl_v5_without_knowledge/joint_intent_slots_knowledge_model.py:221
↓ 1 callersMethodloss_seq2seq
(self)
joint_model_knowl_v7_with_domain_knowledge_context_window/joint_intent_slots_knowledge_domain_model.py:228
↓ 1 callersMethodloss_seq2seq
(self)
joint_model_knowl_v0/a1_joint_intent_slots_model.py:169
↓ 1 callersMethodloss_seq2seq
(self)
joint_model_knowl_v3_bi_directional_cnn_tmall/joint_intent_slots_knowledge_model.py:214
↓ 1 callersMethodloss_seq2seq
(self)
joint_model_knowl_v8_slot_condition_intent/joint_intent_slots_knowledge_conditional_model.py:242
↓ 1 callersMethodloss_seq2seq
(self)
joint_model_naive_v1/joint_intent_slots_naive_model.py:100
↓ 1 callersFunctionmulti_head_attention
the current target hidden state is compared with all source states to derive attention weights. score=V_a.tanh(W1*h_t + W2_H_s) :param curren
resources/a1_seq2seq.py:214
↓ 1 callersFunctionmulti_head_attention
the current target hidden state is compared with all source states to derive attention weights. score=V_a.tanh(W1*h_t + W2_H_s) :param curren
joint_model_knowl_v0/a1_seq2seq.py:214
↓ 1 callersFunctionmultiplication_attention_get_weights
the current target hidden state is compared with all source states to derive attention weights. score=qWc*normalized :param current_target_hi
resources/a1_seq2seq.py:168
↓ 1 callersFunctionmultiplication_attention_get_weights
the current target hidden state is compared with all source states to derive attention weights. score=qWc*normalized :param current_target_hi
joint_model_knowl_v0/a1_seq2seq.py:168
↓ 1 callersFunctionpredict_interactive
()
joint_model_knowl_v2_simpl_modl_feat/joint_intent_slots_knowledge_predict.py:108
↓ 1 callersFunctionpredict_interactive
()
joint_model_knowl_v6_with_domain_knowledge/joint_intent_slots_knowledge_domain_predict.py:196
↓ 1 callersFunctionpredict_interactive
()
joint_model_knowl_v4_cnn_with_symbol_alime/joint_intent_slots_knowledge_predict.py:188
↓ 1 callersFunctionpredict_interactive
()
joint_model_knowl_v5_without_knowledge/joint_intent_slots_knowledge_predict.py:188
↓ 1 callersFunctionpredict_interactive
()
joint_model_knowl_v7_with_domain_knowledge_context_window/joint_intent_slots_knowledge_domain_predict.py:195
↓ 1 callersFunctionpredict_interactive
()
joint_model_knowl_v3_bi_directional_cnn_tmall/joint_intent_slots_knowledge_predict.py:188
↓ 1 callersFunctionpredict_interactive
()
joint_model_knowl_v8_slot_condition_intent/joint_intent_slots_knowledge_conditional_predict.py:232
↓ 1 callersFunctionpredict_interactive
()
joint_model_naive_v1/joint_intent_slots_navie_predict.py:80
↓ 1 callersFunctionprocess_qa
(file_name, word2id_x, sequence_length)
joint_model_knowl_v6_with_domain_knowledge/a1_data_util.py:71
↓ 1 callersFunctionprocess_qa
(file_name,word2id_x,sequence_length)
joint_model_knowl_v4_cnn_with_symbol_alime/a1_data_util.py:65
↓ 1 callersFunctionprocess_qa
(file_name,word2id_x,sequence_length)
joint_model_knowl_v5_without_knowledge/a1_data_util.py:65
↓ 1 callersFunctionprocess_qa
(file_name, word2id_x, sequence_length)
joint_model_knowl_v7_with_domain_knowledge_context_window/a1_data_util.py:71
↓ 1 callersFunctionprocess_qa
(file_name,word2id_x,sequence_length)
joint_model_knowl_v3_bi_directional_cnn_tmall/a1_data_util.py:65
↓ 1 callersFunctionprocess_qa
(file_name, word2id_x, sequence_length)
joint_model_knowl_v8_slot_condition_intent/a1_data_util.py:71
↓ 1 callersFunctionrnn_decoder_with_attention
RNN decoder for the sequence-to-sequence model. Args: decoder_inputs: A list of 2D Tensors [batch_size x input_size].it is decoder input.
resources/a1_seq2seq.py:23
↓ 1 callersFunctionrnn_decoder_with_attention
RNN decoder for the sequence-to-sequence model. Args: decoder_inputs: A list of 2D Tensors [batch_size x input_size].it is decoder input.
joint_model_knowl_v0/a1_seq2seq.py:23
↓ 1 callersMethodsimiliarity_module
(self)
joint_model_knowl_v9_intent_rank/joint_intent_slots_knowledge_rank_model.py:166
↓ 1 callersMethodsimiliarity_module
(self)
joint_model_knowl_v6_with_domain_knowledge/joint_intent_slots_knowledge_domain_model.py:159
↓ 1 callersMethodsimiliarity_module
(self)
joint_model_knowl_v4_cnn_with_symbol_alime/joint_intent_slots_knowledge_model.py:146
↓ 1 callersMethodsimiliarity_module
(self)
joint_model_knowl_v5_without_knowledge/joint_intent_slots_knowledge_model.py:146
↓ 1 callersMethodsimiliarity_module
(self)
joint_model_knowl_v7_with_domain_knowledge_context_window/joint_intent_slots_knowledge_domain_model.py:154
↓ 1 callersMethodsimiliarity_module
(self)
joint_model_knowl_v3_bi_directional_cnn_tmall/joint_intent_slots_knowledge_model.py:150
↓ 1 callersMethodsimiliarity_module
(self)
joint_model_knowl_v8_slot_condition_intent/joint_intent_slots_knowledge_conditional_model.py:169
↓ 1 callersFunctiontest_jieba
(string)
resources/a1_test.py:9
↓ 1 callersFunctiontokenize_sentence
tokenize sentence
resources/a1_test.py:19
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