class_docstr: Convert an image from YUV to RGB.
  
  The image data is assumed to be in the range of (0, 1) for luma and (-0.5, 0.5) for chroma.
  
  Returns:
      RGB version of the image.
  
  Shape:
      - image: :math:`(*, 3, H, W)`
      - output: :math:`(*, 3, H, W)`
  
  Examples:
      >>> input = torch.rand(2, 3, 4, 5)
      >>> rgb = YuvToRgb()
      >>> output = rgb(input)  # 2x3x4x5
class_docstr_tok: ["Convert","an","image","from","YUV","to","RGB",".","The","image","data","is","assumed","to","be","in","the","range","of","(","0",",","1",")","for","luma","and","(","-0.5",",","0.5",")","for","chroma",".","Returns",":","RGB","version","of","the","image",".","Shape",":","-","image",":",":","math",":","`","(","*",",","3",",","H",",","W",")","`","-","output",":",":","math",":","`","(","*",",","3",",","H",",","W",")","`","Examples",":",">",">",">","input","=","torch.rand","(","2",",","3",",","4",",","5",")",">",">",">","rgb","=","YuvToRgb","(",")",">",">",">","output","=","rgb","(","input",")","#","2x3x4x5"]
code: def forward(self, input: torch.Tensor) -> torch.Tensor:
      return yuv_to_rgb(input)
  
imports: from typing import Tuple
  import torch
  from torch import nn
label_desc: Use image node_id 1 for calling the YuvToRgb obj's underlying member method code with example usage: obj.forward(input) and returns: yuv_to_rgb