code: def test_to_tensor(self):
      cloud = self.init_cloud(5, 100, 10, lists_to_tensors=True)
      device = torch.device("cuda:1")
  
      new_cloud = cloud.to(device)
      self.assertTrue(new_cloud.device == device)
      self.assertTrue(cloud.device == torch.device("cuda:0"))
      for attrib in [
          "points_padded",
          "points_packed",
          "normals_padded",
          "normals_packed",
          "features_padded",
          "features_packed",
          "num_points_per_cloud",
          "cloud_to_packed_first_idx",
          "padded_to_packed_idx",
      ]:
          self.assertClose(
              getattr(new_cloud, attrib)().cpu(),
              getattr(cloud, attrib)().cpu(),
          )
      for i in range(len(cloud)):
          self.assertClose(
              cloud.points_list()[i].cpu(),
              new_cloud.points_list()[i].cpu(),
          )
          self.assertClose(
              cloud.normals_list()[i].cpu(),
              new_cloud.normals_list()[i].cpu(),
          )
          self.assertClose(
              cloud.features_list()[i].cpu(),
              new_cloud.features_list()[i].cpu(),
          )
      self.assertTrue(all(cloud.valid.cpu() == new_cloud.valid.cpu()))
      self.assertTrue(cloud.equisized == new_cloud.equisized)
      self.assertTrue(cloud._N == new_cloud._N)
      self.assertTrue(cloud._P == new_cloud._P)
      self.assertTrue(cloud._C == new_cloud._C)
  
imports: import itertools
  import random
  import unittest
  import numpy
  import torch
  from pytorch3d.structures import utils
  from pytorch3d.structures.pointclouds import join_pointclouds_as_batch, join_pointclouds_as_scene, Pointclouds
  from .common_testing import TestCaseMixin
label_desc: Use image node_id 19 for calling the TestPointclouds obj's underlying member method code with example usage: obj.test_to_tensor() without return types