class_docstr: Undoes the normalization and returns the reconstructed images in the input domain.
class_docstr_tok: ["Undoes","the","normalization","and","returns","the","reconstructed","images","in","the","input","domain","."]
code: def __init__(self, mean, std):
      mean = torch.as_tensor(mean)
      std = torch.as_tensor(std)
      std_inv = 1 / (std + 1e-7)
      mean_inv = -mean * std_inv
      super().__init__(mean=mean_inv, std=std_inv)
  
file_path: insightface/parsing/dml_csr/utils/utils.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import torchvision
  import torch
  from PIL import Image
  from torch import nn
label_desc: Use image node_id 1 to create a new NormalizeInverse object from inherited base classes: torchvision.transforms with example: obj = NormalizeInverse(mean, std)