code: def posterize(img: Tensor, bits: int) -> Tensor:
      _assert_image_tensor(img)
  
      if img.ndim < 3:
          raise TypeError(
              f"Input image tensor should have at least 3 dimensions, but found {img.ndim}"
          )
      if img.dtype != torch.uint8:
          raise TypeError(
              f"Only torch.uint8 image tensors are supported, but found {img.dtype}"
          )
  
      _assert_channels(img, [1, 3])
      mask = -int(
          2 ** (8 - bits)
      )  # JIT-friendly for: ~(2 ** (8 - bits) - 1)
      return img & mask
  
imports: import warnings
  from typing import List, Optional, Tuple, Union
  import torch
  from torch import Tensor
  from torch.nn.functional import conv2d, grid_sample, interpolate, pad
label_desc: Use image node_id 39 for calling a global function with example usage: posterize(img, bits) and returns: unknown