code: def normalize_keypoints(kpts: Tensor, size: Tensor) -> Tensor:
      if isinstance(size, torch.Size):
          size = tensor(size)[None]
      shift = size.float().to(kpts) / 2
      scale = size.max(1).values.float().to(kpts) / 2
      kpts = (kpts - shift[:, None]) / scale[:, None, None]
      return kpts
  
label_desc: Use image node_id 1 for calling a global function with example usage: normalize_keypoints(kpts, size) and returns: kpts