def spatial_average2d()

in benchmarks/horovod-resnet/train_imagenet_resnet_hvd.py [0:0]

• 9 lines of code
• 3 McCabe index (conditional complexity)

    def spatial_average2d(self, inputs):
        shape = inputs.get_shape().as_list()
        if self.data_format == "channels_last":
            n, h, w, c = shape
        else:
            n, c, h, w = shape
        n = -1 if n is None else n
        x = tf.layers.average_pooling2d(inputs, (h, w), (1, 1), data_format=self.data_format)
        return tf.reshape(x, [n, c])