code: def render_cubified_voxels(
      voxels: torch.Tensor,
      shader_type=HardPhongShader,
      device: Device = "cpu",
      **kwargs,
  ):  # pragma: no cover
      """
      Use the Cubify operator to convert inputs voxels to a mesh and then render that mesh.
  
      Args:
          voxels: FloatTensor of shape (N, D, D, D) where N is the batch size and
              D is the number of voxels along each dimension.
          shader_type: shader_type: shader_type: Shader to use for rendering. Examples
              include HardPhongShader (default), SoftPhongShader etc or any other type
              of valid Shader class.
          device: Device (as str or torch.device) on which the tensors should be located.
          **kwargs: Accepts any of the kwargs that the renderer supports.
      Returns:
          Batch of rendered images of shape (N, H, W, 3).
      """
      cubified_voxels = cubify(voxels, CUBIFY_THRESH).to(device)
      cubified_voxels.textures = TexturesVertex(
          verts_features=torch.ones_like(
              cubified_voxels.verts_padded(), device=device
          )
      )
      cameras = BlenderCamera(device=device)
      renderer = MeshRenderer(
          rasterizer=MeshRasterizer(
              cameras=cameras,
              raster_settings=kwargs.get(
                  "raster_settings", RasterizationSettings()
              ),
          ),
          shader=shader_type(
              device=device,
              cameras=cameras,
              lights=kwargs.get("lights", PointLights()).to(device),
          ),
      )
      return renderer(cubified_voxels)
  
imports: import math
  from typing import Dict, List
  import numpy
  import torch
  from pytorch3d.common.datatypes import Device
  from pytorch3d.datasets.utils import collate_batched_meshes
  from pytorch3d.ops import cubify
  from pytorch3d.renderer import HardPhongShader, MeshRasterizer, MeshRenderer, PointLights, RasterizationSettings, TexturesVertex
  from pytorch3d.renderer.cameras import CamerasBase
  from pytorch3d.transforms import Transform3d
label_desc: Use image node_id 9 for calling a global function with example usage: render_cubified_voxels(voxels, shader_type, device) and returns: renderer