class_docstr: Convert an image from HLS to RGB.
  
  The image data is assumed to be in the range of (0, 1).
  
  Returns:
      RGB version of the image.
  
  Shape:
      - input: :math:`(*, 3, H, W)`
      - output: :math:`(*, 3, H, W)`
  
  Reference:
      https://en.wikipedia.org/wiki/HSL_and_HSV
  
  Examples:
      >>> input = torch.rand(2, 3, 4, 5)
      >>> rgb = HlsToRgb()
      >>> output = rgb(input)  # 2x3x4x5
class_docstr_tok: ["Convert","an","image","from","HLS","to","RGB",".","The","image","data","is","assumed","to","be","in","the","range","of","(","0",",","1",")",".","Returns",":","RGB","version","of","the","image",".","Shape",":","-","input",":",":","math",":","`","(","*",",","3",",","H",",","W",")","`","-","output",":",":","math",":","`","(","*",",","3",",","H",",","W",")","`","Reference",":","https",":","\/\/en.wikipedia.org\/wiki\/HSL_and_HSV","Examples",":",">",">",">","input","=","torch.rand","(","2",",","3",",","4",",","5",")",">",">",">","rgb","=","HlsToRgb","(",")",">",">",">","output","=","rgb","(","input",")","#","2x3x4x5"]
code: def forward(self, image: Tensor) -> Tensor:
      return hls_to_rgb(image)
  
file_path: kornia/kornia/color/hls.py
imports: import math
  from typing import Tuple
  import torch
  from kornia.core import Module, Tensor, stack, tensor, where
label_desc: Use image node_id 1 for calling the HlsToRgb obj's underlying member method code with example usage: obj.forward(image) and returns: hls_to_rgb