import tensorflow as tf

                im = tf.concat([a, b, c], axis=3)
                im = tf.transpose(im, [0, 2, 3, 1])
                im = (im + 1.0) * 128
                im = tf.clip_by_value(im, 0, 255)
                im = tf.cast(im, tf.uint8, name='viz')
            tf.summary.image(name, im, max_outputs=50)

        # use the initializers from torch
        with argscope([Conv2D, Deconv2D], use_bias=False,
                      W_init=tf.random_normal_initializer(stddev=0.02)), \
