import tensorflow as tf

            (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}
            )

            if FLAGS.attack_method == 'carliniL2_specific' or FLAGS.attack_method == 'carliniL2_highden':
                print('Log-density-ratio in attacking function of nor/adv is %f'%np.sum(log_density_ratio))
                m_tsne_logits_adv = (copy.copy(logits_part_adv)).reshape((1, 64))
