code: def inverse_normalize(self, batch_img):
      if self.UN_Normalize:
          batch_img[:, 0, :, :] = (
              batch_img[:, 0, :, :] * self.normalize_std[0]
              + self.normalize_mean[0]
          )
          batch_img[:, 1, :, :] = (
              batch_img[:, 1, :, :] * self.normalize_std[1]
              + self.normalize_mean[1]
          )
          batch_img[:, 2, :, :] = (
              batch_img[:, 2, :, :] * self.normalize_std[2]
              + self.normalize_mean[2]
          )
  
imports: import os
  import pathlib
  import shutil
  from pprint import pformat
  import anyconfig
  import paddle
  import numpy
  import random
  from paddle.jit import to_static
  from paddle.static import InputSpec
  from utils import setup_logger
label_desc: Use image node_id 13 for calling the BaseTrainer obj's underlying member method code with example usage: obj.inverse_normalize(batch_img) without return types