code: def batch_per_image_standardization(imgs):
      # replicate tf.image.per_image_standardization, but in batch
      assert imgs.ndimension() == 4
      mean = (
          imgs.view(imgs.shape[0], -1)
          .mean(dim=1)
          .view(imgs.shape[0], 1, 1, 1)
      )
      return (imgs - mean) / batch_adjusted_stddev(imgs)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 25 for calling a global function with example usage: batch_per_image_standardization(imgs) and returns: unknown