code: def save_image(
      tensor: Union[torch.Tensor, List[torch.Tensor]],
      fp: Union[str, pathlib.Path, BinaryIO],
      format: Optional[str] = None,
      **kwargs,
  ) -> None:
      """
      Save a given Tensor into an image file.
  
      Args:
          tensor (Tensor or list): Image to be saved. If given a mini-batch tensor,
              saves the tensor as a grid of images by calling ``make_grid``.
          fp (string or file object): A filename or a file object
          format(Optional):  If omitted, the format to use is determined from the filename extension.
              If a file object was used instead of a filename, this parameter should always be used.
          **kwargs: Other arguments are documented in ``make_grid``.
      """
  
      if not torch.jit.is_scripting() and not torch.jit.is_tracing():
          _log_api_usage_once(save_image)
      grid = make_grid(tensor, **kwargs)
      # Add 0.5 after unnormalizing to [0, 255] to round to the nearest integer
      ndarr = (
          grid.mul(255)
          .add_(0.5)
          .clamp_(0, 255)
          .permute(1, 2, 0)
          .to("cpu", torch.uint8)
          .numpy()
      )
      im = Image.fromarray(ndarr)
      im.save(fp, format=format)
  
imports: import collections
  import math
  import pathlib
  import warnings
  from itertools import repeat
  from types import FunctionType
  from typing import Any, BinaryIO, List, Optional, Tuple, Union
  import numpy
  import torch
  from PIL import Image, ImageColor, ImageDraw, ImageFont
label_desc: Use image node_id 2 for calling a global function with example usage: save_image(tensor, fp, format) without return types