code: def adjust_saturation(
      inpt: torch.Tensor, saturation_factor: float
  ) -> torch.Tensor:
      """Adjust saturation."""
      if torch.jit.is_scripting():
          return adjust_saturation_image(
              inpt, saturation_factor=saturation_factor
          )
  
      _log_api_usage_once(adjust_saturation)
  
      kernel = _get_kernel(adjust_saturation, type(inpt))
      return kernel(inpt, saturation_factor=saturation_factor)
  
imports: from typing import List
  import PIL.Image
  import torch
  from torch.nn.functional import conv2d
  from torchvision import tv_tensors
  from torchvision.transforms import _functional_pil
  from torchvision.transforms._functional_tensor import _max_value
  from torchvision.utils import _log_api_usage_once
  from ._misc import _num_value_bits, to_dtype_image
  from ._type_conversion import pil_to_tensor, to_pil_image
  from ._utils import _get_kernel, _register_kernel_internal
label_desc: Use image node_id 10 for calling a global function with example usage: adjust_saturation(inpt, saturation_factor) and returns: kernel, adjust_saturation_image