code: def linear_rgb_to_rgb(image: torch.Tensor) -> torch.Tensor:
      r"""Convert a linear RGB image to sRGB. Used in colorspace conversions.
  
      Args:
          image: linear RGB Image to be converted to sRGB of shape :math:`(*,3,H,W)`.
  
      Returns:
          sRGB version of the image with shape of shape :math:`(*,3,H,W)`.
  
      Example:
          >>> input = torch.rand(2, 3, 4, 5)
          >>> output = linear_rgb_to_rgb(input) # 2x3x4x5
      """
      if not isinstance(image, torch.Tensor):
          raise TypeError(
              f"Input type is not a torch.Tensor. Got {type(image)}"
          )
  
      if len(image.shape) < 3 or image.shape[-3] != 3:
          raise ValueError(
              f"Input size must have a shape of (*, 3, H, W).Got {image.shape}"
          )
  
      threshold = 0.0031308
      rgb: torch.Tensor = torch.where(
          image > threshold,
          1.055 * torch.pow(image.clamp(min=threshold), 1 / 2.4)
          - 0.055,
          12.92 * image,
      )
  
      return rgb
  
imports: from typing import Union, cast
  import torch
  from torch import nn
label_desc: Use image node_id 8 for calling a global function with example usage: linear_rgb_to_rgb(image) and returns: rgb