text: import torch
  from torch import nn
  
  class Normalize(nn.Module):
      """ ImageNet normalization """
      def __init__(self, mean, std):
          super().__init__()
          self.mean = nn.Parameter(torch.tensor(mean), requires_grad=False)
          self.std = nn.Parameter(torch.tensor(std), requires_grad=False)
  
      def forward(self, x):
          return (x - self.mean[None,:,None,None]) / self.std[None,:,None,None]