class_docstr: Module to convert a bayer raw image to RGB version of image.
  
  The image data is assumed to be in the range of (0, 1).
  
  Shape:
      - image: :math:`(*, 1, H, W)`
      - output: :math:`(*, 3, H, W)`
  
  Example:
      >>> rawinput = torch.rand(2, 1, 4, 6)
      >>> rgb = RawToRgb(CFA.RG)
      >>> output = rgb(rawinput)  # 2x3x4x5
class_docstr_tok: ["Module","to","convert","a","bayer","raw","image","to","RGB","version","of","image",".","The","image","data","is","assumed","to","be","in","the","range","of","(","0",",","1",")",".","Shape",":","-","image",":",":","math",":","`","(","*",",","1",",","H",",","W",")","`","-","output",":",":","math",":","`","(","*",",","3",",","H",",","W",")","`","Example",":",">",">",">","rawinput","=","torch.rand","(","2",",","1",",","4",",","6",")",">",">",">","rgb","=","RawToRgb","(","CFA.RG",")",">",">",">","output","=","rgb","(","rawinput",")","#","2x3x4x5"]
code: def forward(self, image: torch.Tensor) -> torch.Tensor:
      return raw_to_rgb(image, cfa=self.cfa)
  
imports: from enum import Enum
  import torch
  from torch import nn
  from kornia.core import Module, Tensor, concatenate
  from kornia.core.check import KORNIA_CHECK, KORNIA_CHECK_SHAPE
label_desc: Use image node_id 2 for calling the RawToRgb obj's underlying member method code with example usage: obj.forward(image) and returns: raw_to_rgb