code: def generation_image(
      id, org_img, org_label, adv_img, adv_label, attack_method="FGSM"
  ):
      """
      save image from array that original or adversarial
      imagenet data set
      Args:
           org_img: array data of test img
           adv_img: array data of adv img
           org_label: the inference label of test image
           adv_label: the adverarial label of adv image
           attack_method: the adverarial example generation method
      """
      DATA_TYPE = "imagenet"
      check_output_directory(DATA_TYPE)
  
      org_path = (
          OUTPUT
          + DATA_TYPE
          + "/%d_original-%d-by-%s.png" % (id, org_label, attack_method)
      )
      adv_path = (
          OUTPUT
          + DATA_TYPE
          + "/%d_adversary-%d-by-%s.png"
          % (id, adv_label, attack_method)
      )
      diff_path = (
          OUTPUT
          + DATA_TYPE
          + "/%d_diff-x-by-%s.png" % (id, attack_method)
      )
  
      org_output = convert_net(org_img)
      adv_output = convert_net(adv_img)
      diff_output = abs(adv_output - org_output)
  
      save_gragh(org_output, org_path)
      save_gragh(adv_output, adv_path)
      save_gragh(diff_output, diff_path)
      print("--------------------------------------------------")
  
file_path: AdvBox/example/utility.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import distutils.util
  import numpy
  from PIL import Image
  import os
  from paddle.fluid import core
label_desc: Use image node_id 6 for calling a global function with example usage: generation_image(id, org_img, org_label, adv_img, adv_label, attack_method) without return types