import tensorflow as tf

          [tf.reduce_mean(inputs_means), tf.reduce_mean(inputs_vars)],
          "image mean and average var",
          first_n=1)

    joint = tf.concat([inputs, G], 0)
    log.info('Input size of unlabelled and generated %s' % (joint.get_shape()))
    self.end_points_D = self.model.discriminator(
        joint, True, None, num_classes=num_classes, batch_size=batch_size_train)
