code: def stack_4d_tensor_to_3d(arr):
      n = arr.shape[0]
      H = int(np.ceil(np.sqrt(n)))
      W = int(np.ceil(n / H))
      n_add = H * W - n
      arr = torch.cat(
          (arr, torch.zeros_like(arr[:1]).repeat(n_add, 1, 1, 1))
      )
      rows = torch.chunk(arr, chunks=W, dim=0)
      arr3d = torch.cat(
          [torch.cat(list(row), dim=2) for row in rows], dim=1
      )
      return arr3d
  
imports: import unittest
  from functools import partial
  from itertools import product
  from typing import Tuple
  import numpy
  import torch
  from pytorch3d.ops import add_pointclouds_to_volumes, add_points_features_to_volume_densities_features
  from pytorch3d.ops.points_to_volumes import _points_to_volumes
  from pytorch3d.ops.sample_points_from_meshes import sample_points_from_meshes
  from pytorch3d.structures.meshes import Meshes
  from pytorch3d.structures.pointclouds import Pointclouds
  from pytorch3d.structures.volumes import Volumes
  from pytorch3d.transforms.so3 import so3_exp_map
  from .common_testing import TestCaseMixin
label_desc: Use image node_id 3 for calling the TestPointsToVolumes obj's underlying member method code with example usage: obj.stack_4d_tensor_to_3d(arr) and returns: arr3d