import tensorflow as tf


        for i in six.moves.range(FLAGS.eval_batch_count):
            time_start = time.time()
            (nor_img,true_label) = sess.run([images,labels])
            adv_img = sess.run(adv_image_craft,feed_dict={image:nor_img})

            # Local logits
            (predict_NOR, predict_ADV, logits_part_nor, logits_part_adv) = sess.run(
                [predict_nor, predict_adv, tsne_logit_nor, tsne_logit_adv],
                feed_dict={image: nor_img, adv_image: adv_img}
            )

            # Local entropy and confidence for nor_img
            (entropy_test_nor_help, labels_nor_help, confidence_test_nor_help) = sess.run(
                [entropy, tf.argmax(predict, axis=1), tf.reduce_max(predict, axis=1)], feed_dict={predict: predict_NOR}
            )

            # Local entropy and confidence for adv_img
            (entropy_test_adv_help, labels_adv_help, confidence_test_adv_help) = sess.run(
                [entropy, tf.argmax(predict, axis=1), tf.reduce_max(predict, axis=1)], feed_dict={predict: predict_ADV}
            )

            entropy_test_adv_all = np.concatenate((entropy_test_adv_all, entropy_test_adv_help), axis=0)
            confidence_test_adv_all = np.concatenate((confidence_test_adv_all, confidence_test_adv_help), axis=0)
            entropy_test_nor_all = np.concatenate((entropy_test_nor_all, entropy_test_nor_help), axis=0)
            confidence_test_nor_all = np.concatenate((confidence_test_nor_all, confidence_test_nor_help), axis=0)
            logits_nor_all = np.concatenate((logits_nor_all, logits_part_nor), axis=0)
            labels_nor_all = np.concatenate((labels_nor_all, labels_nor_help), axis=0)
