class_docstr: Base class for volume rendering.
  
  Implementation follows Ben Mildenhall et el. (2020) at https://arxiv.org/abs/2003.08934.
class_docstr_tok: ["Base","class","for","volume","rendering",".","Implementation","follows","Ben","Mildenhall","et","el",".","(","2020",")","at","https",":","\/\/arxiv.org\/abs\/2003.08934","."]
docstr: Initializes the renderer.
  
  Args:
      shift: Size of far-field layer: int
docstr_tok: ["Initializes","the","renderer",".","Args",":","shift",":","Size","of","far-field","layer",":","int"]
code: def __init__(self, shift: int = 1) -> None:
      """Initializes the renderer.
  
      Args:
          shift: Size of far-field layer: int
      """
      super().__init__()
      self._shift = shift
  
file_path: kornia/kornia/nerf/volume_renderer.py
imports: import torch
  from kornia.core import Tensor
  from kornia.core.check import KORNIA_CHECK_SHAPE
  from kornia.nerf.samplers import calc_ray_t_vals
label_desc: Use image node_id 1 to create a new VolumeRenderer object from inherited base classes: torch.nn with example: obj = VolumeRenderer(shift)