inference.py 文件源码

def build_model(chunk_size, feature_len, num_classes, gru_size=128):
    """Builds a bidirectional GRU model"""

    model = Sequential()
    # Bidirectional wrapper takes a copy of the first argument and reverses
    #   the direction. Weights are independent between components.
    model.add(Bidirectional(
        GRU(gru_size, activation='tanh', return_sequences=True, name='gru1'),
        input_shape=(chunk_size, feature_len))
    )
    model.add(Bidirectional(
        GRU(gru_size, activation='tanh', return_sequences=True, name='gru2'))
    )
    model.add(Dense(num_classes, activation='softmax', name='classify'))
    return model