test_keras2_numeric.py 文件源码

def test_tiny_conv_prelu_random(self,
                                    model_precision=_MLMODEL_FULL_PRECISION):
        np.random.seed(1988)

        # Define a model
        from keras.layers.advanced_activations import PReLU
        model = Sequential()
        model.add(Conv2D(input_shape = (10, 10, 3),
            filters = 3, kernel_size = (5,5), padding = 'same'))
        model.add(PReLU(shared_axes=[1, 2]))

        model.set_weights([np.random.rand(*w.shape) for w in model.get_weights()])

        # Get the coreml model
        self._test_keras_model(model, model_precision=model_precision)