models.py 文件源码

def pure_rnn_3(input_shape, n_classes):
    """
    just replace ANN by 3xRNNs
    """
    model = Sequential(name='pure_rnn')
    model.add(LSTM(80, return_sequences=True, input_shape=input_shape))
    model.add(LSTM(80, return_sequences=True))
    model.add(LSTM(50, return_sequences=False))
    model.add(Dense(n_classes, activation = 'softmax'))
    model.compile(loss='categorical_crossentropy', optimizer=Adam(), metrics=[keras.metrics.categorical_accuracy])
    return model



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