import tensorflow as tf

        num_adv = int(hps.batch_size/10)
        print('num_adv is %d'%(num_adv))
    else:
        num_adv = hps.batch_size

    for i in six.moves.range(num_batch):
        print(i)
        (logits_part_nor, logits_part_adv, labels_part) = sess.run([logits_nor, logits_adv, tf.argmax(labels, 1)])
        logits_all = np.concatenate((logits_all, logits_part_nor), axis=0)
        labels_all = np.concatenate((labels_all, labels_part), axis=0)
        is_adv_all = np.concatenate((is_adv_all, np.zeros(hps.batch_size)), axis=0)
        logits_all = np.concatenate((logits_all, logits_part_adv[:num_adv]), axis=0)
        labels_all = np.concatenate((labels_all, labels_part[:num_adv]), axis=0)
        is_adv_all = np.concatenate((is_adv_all, np.ones(num_adv)), axis=0)
