test_keras_numeric.py 文件源码

def test_medium_conv_batchnorm_random(self):
        np.random.seed(1988)
        input_dim = 10
        input_shape = (input_dim, input_dim, 3)
        num_kernels = 3
        kernel_height = 5
        kernel_width = 5
        data_mean = 2
        data_var = 1

        # Define a model
        from keras.layers.normalization import BatchNormalization
        model = Sequential()
        model.add(Convolution2D(input_shape = input_shape,
            nb_filter = num_kernels, nb_row = kernel_height,
            nb_col = kernel_width))
        model.add(BatchNormalization(epsilon=1e-5))

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

        # Get the coreml model
        self._test_keras_model(model)