code: def sample_points_with_init(
      num_meshes: int,
      num_verts: int,
      num_faces: int,
      num_samples: int,
      device: str = "cpu",
  ):
      verts_list = []
      faces_list = []
      for _ in range(num_meshes):
          verts = torch.rand(
              (num_verts, 3), dtype=torch.float32, device=device
          )
          faces = torch.randint(
              num_verts,
              size=(num_faces, 3),
              dtype=torch.int64,
              device=device,
          )
          verts_list.append(verts)
          faces_list.append(faces)
      meshes = Meshes(verts_list, faces_list)
      torch.cuda.synchronize()
  
      def sample_points():
          sample_points_from_meshes(
              meshes, num_samples=num_samples, return_normals=True
          )
          torch.cuda.synchronize()
  
      return sample_points
  
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 10 for calling the TestSamplePoints obj's underlying member method code with example usage: obj.sample_points_with_init(num_meshes, num_verts, num_faces, num_samples, device) and returns: sample_points