test_keras.py 文件源码

def test_conv1d_lstm(self):
        from keras.layers import Convolution1D, LSTM, Dense
        model = Sequential()
        # input_shape = (time_step, dimensions)
        model.add(Convolution1D(32,3,border_mode='same',input_shape=(10,8)))
        # conv1d output shape = (None, 10, 32)
        model.add(LSTM(24))
        model.add(Dense(1, activation='sigmoid'))
        print('model.layers[1].output_shape=', model.layers[1].output_shape)

        input_names = ['input']
        output_names = ['output']
        spec = keras.convert(model, input_names, output_names).get_spec()

        self.assertIsNotNone(spec)
        self.assertTrue(spec.HasField('neuralNetwork'))

        # Test the inputs and outputs
        self.assertEquals(len(spec.description.input), len(input_names))
        self.assertItemsEqual(input_names,
              map(lambda x: x.name, spec.description.input))
        self.assertEquals(len(spec.description.output), len(output_names))
        self.assertItemsEqual(output_names,
              map(lambda x: x.name, spec.description.output))

        # Test the layer parameters.
        layers = spec.neuralNetwork.layers
        self.assertIsNotNone(layers[0].convolution)
        self.assertIsNotNone(layers[1].simpleRecurrent)
        self.assertIsNotNone(layers[2].innerProduct)