code: def solarize(img: Tensor, threshold: float) -> 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}"
          )
  
      _assert_channels(img, [1, 3])
  
      if threshold > _max_value(img.dtype):
          raise TypeError("Threshold should be less than bound of img.")
  
      inverted_img = invert(img)
      return torch.where(img >= threshold, inverted_img, img)
  
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 40 for calling a global function with example usage: solarize(img, threshold) and returns: torch