class_docstr: Normalizes an image by subtracting the mean and dividing by the
  standard deviation, separately for each channel.
class_docstr_tok: ["Normalizes","an","image","by","subtracting","the","mean","and","dividing","by","the","standard","deviation",",","separately","for","each","channel","."]
code: def forward(self, images: FloatTensor, sizes: IntTensor):
      assert images.size(1) == self.means.size(0)
      self.means = self.means.to(images.device)
      self.stds = self.stds.to(images.device)
      images = images.transpose(1, -1)
      images = images - self.means
      images = images / self.stds
      return images.transpose(-1, 1)
  
file_path: allennlp/allennlp/modules/vision/image2image.py
imports: import torch
  from torch import nn, FloatTensor, IntTensor
  from typing import List
  from allennlp.common.registrable import Registrable
label_desc: Use image node_id 2 for calling the NormalizeImage obj's underlying member method code with example usage: obj.forward(images, sizes) and returns: images