code: def posterize(img: Tensor, bits: int) -> Tensor:
      """Posterize an image by reducing the number of bits for each color channel.
  
      Args:
          img (PIL Image or Tensor): Image to have its colors posterized.
              If img is torch Tensor, it should be of type torch.uint8, and
              it is expected to be in [..., 1 or 3, H, W] format, where ... means
              it can have an arbitrary number of leading dimensions.
              If img is PIL Image, it is expected to be in mode "L" or "RGB".
          bits (int): The number of bits to keep for each channel (0-8).
      Returns:
          PIL Image or Tensor: Posterized image.
      """
      if not torch.jit.is_scripting() and not torch.jit.is_tracing():
          _log_api_usage_once(posterize)
      if not (0 <= bits <= 8):
          raise ValueError(
              f"The number if bits should be between 0 and 8. Got {bits}"
          )
  
      if not isinstance(img, torch.Tensor):
          return F_pil.posterize(img, bits)
  
      return F_t.posterize(img, bits)
  
imports: import math
  import numbers
  import sys
  import warnings
  from enum import Enum
  from typing import Any, List, Optional, Tuple, Union
  import numpy
  import torch
  from PIL import Image
  from torch import Tensor
  from ..utils import _log_api_usage_once
  from .None import _functional_pil, _functional_tensor
label_desc: Use image node_id 37 for calling a global function with example usage: posterize(img, bits) and returns: F_t, F_pil