code: def __call__(self, image, label):
      if self.std is None:
          for t, m in zip(image, self.mean):
              t.sub_(m)
      else:
          for t, m, s in zip(image, self.mean, self.std):
              t.sub_(m).div_(s)
      return image, label
  
imports: import random
  import math
  import numpy
  import numbers
  import collections
  import cv2
  import torch
  import time
label_desc: Use image node_id 2 for calling the Normalize obj's underlying member method code with example usage: obj.__call__(image, label) and returns: image,  label