code: def __init__(self, mean, std):
      super(NormalizeByChannelMeanStd, self).__init__()
      if not isinstance(mean, torch.Tensor):
          mean = torch.tensor(mean)
      if not isinstance(std, torch.Tensor):
          std = torch.tensor(std)
      self.register_buffer("mean", mean)
      self.register_buffer("std", std)
  
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 1 to create a new NormalizeByChannelMeanStd object from inherited base classes: nn with example: obj = NormalizeByChannelMeanStd(mean, std)