test_keras2_numeric.py 文件源码

def test_conv_batchnorm_no_gamma_no_beta(self, model_precision=_MLMODEL_FULL_PRECISION):
        np.random.seed(1988)
        input_dim = 10
        input_shape = (input_dim, input_dim, 3)
        num_kernels = 3
        kernel_height = 5
        kernel_width = 5

        # Define a model
        model = Sequential()
        model.add(Conv2D(input_shape = input_shape, 
            filters = num_kernels, kernel_size = (kernel_height, kernel_width)))
        model.add(BatchNormalization(center=False, scale=False, 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, model_precision=model_precision)