code: def test_inside_box(self):
      def inside_box_naive(cloud, box_min, box_max):
          return (
              (cloud >= box_min.view(1, 3))
              * (cloud <= box_max.view(1, 3))
          ).all(dim=-1)
  
      N, P, C = 5, 100, 4
  
      clouds = self.init_cloud(
          N, P, C, with_normals=False, with_features=False
      )
      device = clouds.device
  
      # box of shape Nx2x3
      box_min = torch.rand((N, 1, 3), device=device)
      box_max = box_min + torch.rand((N, 1, 3), device=device)
      box = torch.cat([box_min, box_max], dim=1)
  
      within_box = clouds.inside_box(box)
  
      within_box_naive = []
      for i, cloud in enumerate(clouds.points_list()):
          within_box_naive.append(
              inside_box_naive(cloud, box[i, 0], box[i, 1])
          )
      within_box_naive = torch.cat(within_box_naive, 0)
      self.assertTrue(torch.equal(within_box, within_box_naive))
  
      # box of shape 2x3
      box2 = box[0, :]
  
      within_box2 = clouds.inside_box(box2)
  
      within_box_naive2 = []
      for cloud in clouds.points_list():
          within_box_naive2.append(
              inside_box_naive(cloud, box2[0], box2[1])
          )
      within_box_naive2 = torch.cat(within_box_naive2, 0)
      self.assertTrue(torch.equal(within_box2, within_box_naive2))
      # box of shape 1x2x3
      box3 = box2.expand(1, 2, 3)
  
      within_box3 = clouds.inside_box(box3)
      self.assertTrue(torch.equal(within_box2, within_box3))
  
      # invalid box
      invalid_box = torch.cat(
          [box_min, box_min - torch.rand((N, 1, 3), device=device)],
          dim=1,
      )
      with self.assertRaisesRegex(ValueError, "Input box is invalid"):
          clouds.inside_box(invalid_box)
  
      # invalid box shapes
      invalid_box = box[0].expand(2, 2, 3)
      with self.assertRaisesRegex(ValueError, "Input box dimension is"):
          clouds.inside_box(invalid_box)
      invalid_box = torch.rand((5, 8, 9, 3), device=device)
      with self.assertRaisesRegex(
          ValueError, "Input box must be of shape"
      ):
          clouds.inside_box(invalid_box)
  
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 26 for calling the TestPointclouds obj's underlying member method code with example usage: obj.test_inside_box() and returns: unknown