code: def test_texture_sampling_cow(self):
      # test texture sampling for the cow example by converting
      # the cow mesh and its texture uv to a pointcloud with texture
  
      device = torch.device("cuda:0")
      obj_dir = get_pytorch3d_dir() / "docs/tutorials/data"
      obj_filename = obj_dir / "cow_mesh/cow.obj"
  
      for text_type in ("uv", "atlas"):
          # Load mesh + texture
          if text_type == "uv":
              mesh = load_objs_as_meshes(
                  [obj_filename],
                  device=device,
                  load_textures=True,
                  texture_wrap=None,
              )
          elif text_type == "atlas":
              mesh = load_objs_as_meshes(
                  [obj_filename],
                  device=device,
                  load_textures=True,
                  create_texture_atlas=True,
                  texture_atlas_size=8,
                  texture_wrap=None,
              )
  
          points, normals, textures = sample_points_from_meshes(
              mesh,
              num_samples=50000,
              return_normals=True,
              return_textures=True,
          )
          pointclouds = Pointclouds(
              points, normals=normals, features=textures
          )
  
          for pos in ("front", "back"):
              # Init rasterizer settings
              if pos == "back":
                  azim = 0.0
              elif pos == "front":
                  azim = 180
              R, T = look_at_view_transform(2.7, 0, azim)
              cameras = FoVPerspectiveCameras(device=device, R=R, T=T)
  
              raster_settings = PointsRasterizationSettings(
                  image_size=512, radius=1e-2, points_per_pixel=1
              )
  
              rasterizer = PointsRasterizer(
                  cameras=cameras, raster_settings=raster_settings
              )
              compositor = NormWeightedCompositor()
              renderer = PointsRenderer(
                  rasterizer=rasterizer, compositor=compositor
              )
              images = renderer(pointclouds)
  
              rgb = images[0, ..., :3].squeeze().cpu()
              if DEBUG:
                  filename = (
                      "DEBUG_cow_mesh_to_pointcloud_%s_%s.png"
                      % (
                          text_type,
                          pos,
                      )
                  )
                  Image.fromarray(
                      (rgb.numpy() * 255).astype(np.uint8)
                  ).save(DATA_DIR / filename)
  
imports: import unittest
  import numpy
  import torch
  from PIL import Image
  from pytorch3d.io import load_objs_as_meshes
  from pytorch3d.ops import sample_points_from_meshes
  from pytorch3d.renderer import TexturesVertex
  from pytorch3d.renderer.cameras import FoVPerspectiveCameras, look_at_view_transform
  from pytorch3d.renderer.mesh.rasterize_meshes import barycentric_coordinates
  from pytorch3d.renderer.points import NormWeightedCompositor, PointsRasterizationSettings, PointsRasterizer, PointsRenderer
  from pytorch3d.structures import Meshes, Pointclouds
  from pytorch3d.utils.ico_sphere import ico_sphere
  from .common_testing import get_pytorch3d_dir, get_random_cuda_device, get_tests_dir, TestCaseMixin
label_desc: Use image node_id 9 for calling the TestSamplePoints obj's underlying member method code with example usage: obj.test_texture_sampling_cow() without return types