code: def imagenet_norm_batch(x):
      mean = torch.tensor([0.485, 0.456, 0.406])[
          None, :, None, None
      ].to(x.device)
      std = torch.tensor([0.229, 0.224, 0.225])[None, :, None, None].to(
          x.device
      )
      x_norm = (x - mean) / std
      return x_norm
  
imports: from __future__ import annotations
  import logging
  import random
  from enum import Enum
  import torch
  import torch.nn.functional
  from torch import Tensor, nn
  from torchvision import transforms
label_desc: Use image node_id 1 for calling a global function with example usage: imagenet_norm_batch(x) and returns: x_norm