class_docstr: Module version of the :func:`raw_to_rgb_2x2_downscaled()` function.
  
  The image width and height have to be divisible by two. The image
  data is assumed to be in the range of (0, 1).
  
  Shape:
      - image: :math:`(*, 1, H, W)`
      - output: :math:`(*, 3, \frac{H}{2}, \frac{W}{2})`
  
  Example:
      >>> rawinput = torch.rand(2, 1, 4, 6)
      >>> rgb_downscale = RawToRgb2x2Downscaled(CFA.RG)
      >>> output = rgb_downscale(rawinput)  # 2x3x2x3
class_docstr_tok: ["Module","version","of","the",":","func",":","`","raw_to_rgb_2x2_downscaled","(",")","`","function",".","The","image","width","and","height","have","to","be","divisible","by","two",".","The","image","data","is","assumed","to","be","in","the","range","of","(","0",",","1",")",".","Shape",":","-","image",":",":","math",":","`","(","*",",","1",",","H",",","W",")","`","-","output",":",":","math",":","`","(","*",",","3",",","\\frac","{","H","}","{","2","}",",","\\frac","{","W","}","{","2","}",")","`","Example",":",">",">",">","rawinput","=","torch.rand","(","2",",","1",",","4",",","6",")",">",">",">","rgb_downscale","=","RawToRgb2x2Downscaled","(","CFA.RG",")",">",">",">","output","=","rgb_downscale","(","rawinput",")","#","2x3x2x3"]
code: def __init__(self, cfa: CFA) -> None:
      super().__init__()
      self.cfa = 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 1 to create a new RawToRgb2x2Downscaled object from inherited base classes: Module with example: obj = RawToRgb2x2Downscaled(cfa)