test_keras2.py 文件源码

def test_simple_rnn(self):
        """
        Test the conversion of a simple RNN layer.
        """
        from keras.layers import SimpleRNN

        # Create a simple Keras model
        model = Sequential()
        model.add(SimpleRNN(32, input_shape=(10,32)))

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

        # Test the model class
        self.assertIsNotNone(spec.description)
        self.assertTrue(spec.HasField('neuralNetwork'))

        # Test the inputs and outputs
        self.assertEquals(len(spec.description.input), len(input_names) + 1)
        self.assertEquals(input_names[0], spec.description.input[0].name)

        self.assertEquals(32, spec.description.input[1].type.multiArrayType.shape[0])

        self.assertEquals(len(spec.description.output), len(output_names) + 1)
        self.assertEquals(output_names[0], spec.description.output[0].name)
        self.assertEquals(32, spec.description.output[0].type.multiArrayType.shape[0])
        self.assertEquals(32, spec.description.output[1].type.multiArrayType.shape[0])

        # Test the layer parameters.
        layers = spec.neuralNetwork.layers
        layer_0 = layers[0]
        self.assertIsNotNone(layer_0.simpleRecurrent)
        self.assertEquals(len(layer_0.input), 2)
        self.assertEquals(len(layer_0.output), 2)