import tensorflow as tf

                "grouped_minibatch_stddev",
                "centered_grouped_image",
                centered_grouped_image
            )

            # Calculate variance over group.
            # shape = (
            #     cur_batch_size / group_size,
            #     image_size,
            #     image_size,
            #     num_channels
            # )
            grouped_variance = tf.reduce_mean(
                input_tensor=tf.square(x=centered_grouped_image),
                axis=0,
                name="grouped_variance"
            )
            print_obj(
                "grouped_minibatch_stddev",
                "grouped_variance",
                grouped_variance
            )

            # Get stddev image using ops common to both grouped & ungrouped.
            stddev_feature_map = self.minibatch_stddev_common(
                variance=grouped_variance,
