RNN-CNN_feature_extract.py 文件源码

def text_feature_extract_model1(embedding_size=128, hidden_size=256):
    '''
    this is a model use normal Bi-LSTM and maxpooling extract feature

    examples:
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??????????????16?12?????????? [  1.59666997e-05]
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    :return:
    '''
    model = Sequential()
    model.add(Embedding(input_dim=max_features,
                        output_dim=embedding_size,
                        input_length=max_seq))
    model.add(Bidirectional(LSTM(hidden_size, return_sequences=True)))
    model.add(TimeDistributed(Dense(embedding_size/2)))
    model.add(Activation('softplus'))
    model.add(MaxPooling1D(5))
    model.add(Flatten())
    # model.add(Dense(2048, activation='softplus'))
    # model.add(Dropout(0.2))
    model.add(Dense(1, activation='sigmoid'))

    model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
    model.summary()
    plot(model, to_file="text_feature_extract_model1.png", show_shapes=True)
    return model