code: def test_padded_to_packed_idx(self):
      device = torch.device("cuda:0")
      points_list = []
      npoints = [10, 20, 30]
      for p in npoints:
          points = torch.rand(
              (p, 3), dtype=torch.float32, device=device
          )
          points_list.append(points)
  
      clouds = Pointclouds(points_list)
  
      padded_to_packed_idx = clouds.padded_to_packed_idx()
      points_packed = clouds.points_packed()
      points_padded = clouds.points_padded()
      points_padded_flat = points_padded.view(-1, 3)
  
      self.assertClose(
          points_padded_flat[padded_to_packed_idx], points_packed
      )
  
      idx = padded_to_packed_idx.view(-1, 1).expand(-1, 3)
      self.assertClose(points_padded_flat.gather(0, idx), points_packed)
  
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 23 for calling the TestPointclouds obj's underlying member method code with example usage: obj.test_padded_to_packed_idx() without return types