code: def lpips(
      x: torch.Tensor,
      y: torch.Tensor,
      net_type: str = "alex",
      version: str = "0.1",
  ):
      r"""Function that measures
      Learned Perceptual Image Patch Similarity (LPIPS).
  
      Arguments:
          x, y (torch.Tensor): the input tensors to compare.
          net_type (str): the network type to compare the features:
                          'alex' | 'squeeze' | 'vgg'. Default: 'alex'.
          version (str): the version of LPIPS. Default: 0.1.
      """
      device = x.device
      criterion = LPIPS(net_type, version).to(device)
      return criterion(x, y)
  
label_desc: Use image node_id 1 for calling a global function with example usage: lpips(x, y, net_type, version) and returns: criterion