import tensorflow as tf

    ul_logit = vat.forward(ul_x, is_training=False, update_batch_stats=False)
    vat_loss = vat.virtual_adversarial_loss(ul_x, ul_u, ul_logit, is_training=False)
    losses['VAT_loss'] = vat_loss
    return losses


def main(_):
    print(FLAGS.epsilon, FLAGS.top_bn)
    np.random.seed(seed=FLAGS.seed)
    tf.set_random_seed(np.random.randint(1234))
    with tf.Graph().as_default() as g:
        with tf.device("/cpu:0"):
            images, labels = inputs(batch_size=FLAGS.batch_size,
                                    train=True,
                                    validation=FLAGS.validation,
                                    shuffle=True)
            ul_images = tf.placeholder(shape=images.shape, dtype=tf.float32)
            '''unlabeled_inputs(batch_size=FLAGS.ul_batch_size,
                                         validation=FLAGS.validation,
                                         shuffle=True)'''
