neon_lstm.py 文件源码

def build_lstm(input_shape):
    model = Sequential()
    # model.add(Masking(input_shape=input_shape, mask_value=-1.))
    model.add(Embedding(input_shape[0], 128, input_length=input_shape[1]))

    model.add(Convolution1D(nb_filter=64,
                            filter_length=5,
                            border_mode='valid',
                            activation='relu',
                            subsample_length=1))
    model.add(MaxPooling1D(pool_length=4))

    model.add(GRU(128))

    # model.add(GRU(128, return_sequences=False))
    # Add dropout if overfitting
    # model.add(Dropout(0.5))
    model.add(Dense(1))
    model.add(Activation('sigmoid'))
    model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
    return model