text: import os
  import sys
  import pytest
  import torch
  from pathlib import Path
  
  from kaolin.rep import TriangleMesh, VoxelGrid, PointCloud
  from kaolin.conversions.meshconversions import trianglemesh_to_pointcloud, trianglemesh_to_voxelgrid
  
  # Skip test if import fails unless on CI and not on Windows
  if os.environ.get('CI') and not sys.platform == 'win32':
      from kaolin.visualize.vis_usd import VisUsd
  else:
      VisUsd = pytest.importorskip('kaolin.visualize.vis_usd.VisUsd', reason='The pxr library could not be imported')
  
  root = Path('tests/visualize/results')
  root.mkdir(exist_ok=True)
  mesh = TriangleMesh.from_obj('tests/model.obj')
  voxels = VoxelGrid(trianglemesh_to_voxelgrid(mesh, 32))
  pc = PointCloud(trianglemesh_to_pointcloud(mesh, 500)[0])
  
  vis = VisUsd()
  
  @pytest.mark.parametrize('object_3d', [mesh, voxels, pc])
  @pytest.mark.parametrize('device', ['cpu', 'cuda'])
  @pytest.mark.parametrize('meet_ground', [True, False])
  @pytest.mark.parametrize('center_on_stage', [True, False])
  @pytest.mark.parametrize('fit_to_stage', [True, False])
  def test_vis(object_3d, device, meet_ground, center_on_stage, fit_to_stage):
      if device == 'cuda':
          if isinstance(object_3d, TriangleMesh):
              object_3d.cuda()
          elif isinstance(object_3d, PointCloud):
              object_3d.points = object_3d.points.to(torch.device(device))
          elif isinstance(object_3d, VoxelGrid):
              object_3d.voxels = object_3d.voxels.to(torch.device(device))
  
      vis.set_stage(filepath=str(root / f'{type(object_3d).__name__}_{device}.usda'))
      vis.visualize(object_3d, meet_ground=meet_ground, center_on_stage=center_on_stage,
                    fit_to_stage=fit_to_stage)
  