Refine understand_sentiment_dynamic_lstm #7004
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dzhwinter
reviewed
Dec 25, 2017
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| inputs = [fc1, lstm1] | ||
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| for i in range(2, stacked_num + 1): | ||
| fc = fluid.layers.fc(input=inputs, size=hid_dim) | ||
| fc = fluid.layers.fc(input=inputs, |
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Please format these lines
dzhwinter
reviewed
Dec 25, 2017
| emb = fluid.layers.embedding( | ||
| input=data, | ||
| size=[input_dim, emb_dim], | ||
| param_attr=ParamAttr(initializer=NormalInitializer( |
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loc default value is .0.
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| fc1 = fluid.layers.fc(input=emb, | ||
| size=hid_dim, | ||
| bias_attr=ParamAttr(initializer=NormalInitializer( |
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Create a ParamAttr, and share it between layers.
| input=fc1, | ||
| size=hid_dim, | ||
| candidate_activation='relu', | ||
| bias_attr=ParamAttr(initializer=NormalInitializer( |
| size=hid_dim, | ||
| is_reverse=(i % 2) == 0, | ||
| candidate_activation='relu', | ||
| bias_attr=ParamAttr(initializer=NormalInitializer( |
| prediction = fluid.layers.fc( | ||
| input=[fc_last, lstm_last], | ||
| size=class_dim, | ||
| bias_attr=ParamAttr(initializer=NormalInitializer( |
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#7003