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san_log.txt
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2018-08-25 03:18:55 [main ] INFO [Launching the SAN]
2018-08-25 03:18:55 [main ] INFO [Loading data]
2018-08-25 03:19:33 [main ] INFO [
############# Model Arch of SAN #############
DNetwork(
(dropout): DropoutWrapper()
(lexicon_encoder): LexiconEncoder(
(dropout): DropoutWrapper()
(dropout_emb): DropoutWrapper()
(dropout_cove): DropoutWrapper()
(embedding): Embedding(90981, 300, padding_idx=0)
(ContextualEmbed): ContextualEmbed(
(embedding): Embedding(90981, 300, padding_idx=0)
(rnn1): LSTM(300, 300, bidirectional=True)
(rnn2): LSTM(600, 300, bidirectional=True)
)
(prealign): AttentionWrapper(
(score_func): SimilarityWrapper(
(score_func): DotProductProject(
(dropout): DropoutWrapper()
(proj_1): Linear(in_features=300, out_features=128, bias=False)
(proj_2): Linear(in_features=300, out_features=128, bias=False)
)
)
)
(pos_embedding): Embedding(54, 12, padding_idx=0)
(ner_embedding): Embedding(41, 8, padding_idx=0)
(doc_pwnn): PositionwiseNN(
(w_0): Conv1d(1224, 256, kernel_size=(1,), stride=(1,))
(w_1): Conv1d(256, 256, kernel_size=(1,), stride=(1,))
(dropout): DropoutWrapper()
)
(que_pwnn): PositionwiseNN(
(w_0): Conv1d(900, 256, kernel_size=(1,), stride=(1,))
(w_1): Conv1d(256, 256, kernel_size=(1,), stride=(1,))
(dropout): DropoutWrapper()
)
)
(doc_encoder_low): OneLayerBRNN(
(dropout): DropoutWrapper()
(rnn): LSTM(856, 128, bidirectional=True)
)
(doc_encoder_high): OneLayerBRNN(
(dropout): DropoutWrapper()
(rnn): LSTM(856, 128, bidirectional=True)
)
(query_encoder_low): OneLayerBRNN(
(dropout): DropoutWrapper()
(rnn): LSTM(856, 128, bidirectional=True)
)
(query_encoder_high): OneLayerBRNN(
(dropout): DropoutWrapper()
(rnn): LSTM(856, 128, bidirectional=True)
)
(query_understand): OneLayerBRNN(
(dropout): DropoutWrapper()
(rnn): LSTM(512, 128, bidirectional=True)
)
(deep_attn): DeepAttentionWrapper(
(dropout): DropoutWrapper()
(attn_list): ModuleList(
(0): AttentionWrapper(
(score_func): SimilarityWrapper(
(score_func): DotProductProject(
(dropout): DropoutWrapper()
(proj_1): Linear(in_features=1412, out_features=128, bias=False)
(proj_2): Linear(in_features=1412, out_features=128, bias=False)
)
)
)
(1): AttentionWrapper(
(score_func): SimilarityWrapper(
(score_func): DotProductProject(
(dropout): DropoutWrapper()
(proj_1): Linear(in_features=1412, out_features=128, bias=False)
(proj_2): Linear(in_features=1412, out_features=128, bias=False)
)
)
)
(2): AttentionWrapper(
(score_func): SimilarityWrapper(
(score_func): DotProductProject(
(dropout): DropoutWrapper()
(proj_1): Linear(in_features=1412, out_features=128, bias=False)
(proj_2): Linear(in_features=1412, out_features=128, bias=False)
)
)
)
)
)
(doc_understand): OneLayerBRNN(
(dropout): DropoutWrapper()
(rnn): LSTM(1280, 128, bidirectional=True)
)
(doc_self_attn): AttentionWrapper(
(score_func): SimilarityWrapper(
(score_func): DotProductProject(
(dropout): DropoutWrapper()
(proj_1): Linear(in_features=2436, out_features=128, bias=False)
(proj_2): Linear(in_features=2436, out_features=128, bias=False)
)
)
)
(doc_mem_gen): OneLayerBRNN(
(dropout): DropoutWrapper()
(rnn): LSTM(512, 128, bidirectional=True)
)
(query_sum_attn): SelfAttnWrapper(
(att): LinearSelfAttn(
(linear): Linear(in_features=256, out_features=1, bias=True)
(dropout): DropoutWrapper()
)
)
(decoder): SAN(
(attn_b): FlatSimilarityWrapper(
(att_dropout): DropoutWrapper()
(score_func): BilinearFlatSim(
(linear): Linear(in_features=256, out_features=256, bias=True)
(dropout): DropoutWrapper()
)
)
(attn_e): FlatSimilarityWrapper(
(att_dropout): DropoutWrapper()
(score_func): BilinearFlatSim(
(linear): Linear(in_features=256, out_features=256, bias=True)
(dropout): DropoutWrapper()
)
)
(rnn): GRUCell(256, 256)
(dropout): DropoutWrapper()
)
)
]
2018-08-25 03:19:33 [main ] INFO [Total number of params: 9194034]
2018-08-25 03:19:35 [main ] WARNING [At epoch 0]
2018-08-25 03:19:36 [main ] INFO [#updates[ 1] train loss[10.12298] remaining[0:35:56]]
2018-08-25 03:20:09 [main ] INFO [#updates[ 100] train loss[8.75332] remaining[0:15:01]]
2018-08-25 03:20:44 [main ] INFO [#updates[ 200] train loss[8.22711] remaining[0:14:33]]
2018-08-25 03:21:18 [main ] INFO [#updates[ 300] train loss[7.78528] remaining[0:13:58]]
2018-08-25 03:21:52 [main ] INFO [#updates[ 400] train loss[7.50866] remaining[0:13:22]]
2018-08-25 03:22:26 [main ] INFO [#updates[ 500] train loss[7.30894] remaining[0:12:47]]
2018-08-25 03:23:01 [main ] INFO [#updates[ 600] train loss[7.16450] remaining[0:12:12]]
2018-08-25 03:23:35 [main ] INFO [#updates[ 700] train loss[7.02247] remaining[0:11:39]]
2018-08-25 03:24:09 [main ] INFO [#updates[ 800] train loss[6.90500] remaining[0:11:04]]
2018-08-25 03:24:43 [main ] INFO [#updates[ 900] train loss[6.82426] remaining[0:10:29]]
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2018-08-25 03:36:16 [main ] INFO [scheduler_type ms]
2018-08-25 03:36:20 [main ] INFO [Saved the new best model and prediction]
2018-08-25 03:36:20 [main ] WARNING [Epoch 0 - dev EM: 55.781 F1: 65.674 (best EM: 55.781 F1: 65.674)]
2018-08-25 03:36:20 [main ] WARNING [At epoch 1]
2018-08-25 03:36:21 [main ] INFO [#updates[ 2739] train loss[5.87273] remaining[0:20:50]]
2018-08-25 03:36:42 [main ] INFO [#updates[ 2800] train loss[5.84832] remaining[0:15:48]]
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2018-08-25 03:53:04 [main ] INFO [scheduler_type ms]
2018-08-25 03:53:08 [main ] INFO [Saved the new best model and prediction]
2018-08-25 03:53:08 [main ] WARNING [Epoch 1 - dev EM: 63.614 F1: 72.870 (best EM: 63.614 F1: 72.870)]
2018-08-25 03:53:08 [main ] WARNING [At epoch 2]
2018-08-25 03:53:09 [main ] INFO [#updates[ 5477] train loss[5.09532] remaining[0:18:25]]
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