code: def iou(N: int, M: int, device="cpu"):
      box = torch.tensor(
          [UNIT_BOX],
          dtype=torch.float32,
          device=device,
      )
      boxes1 = box + torch.randn((N, 1, 3), device=device)
      boxes2 = box + torch.randn((M, 1, 3), device=device)
  
      def output():
          vol, iou = box3d_overlap(boxes1, boxes2)
  
      return output
  
imports: import pickle
  import random
  import unittest
  from typing import List, Tuple, Union
  import torch
  import torch.nn.functional
  from pytorch3d.io import save_obj
  from pytorch3d.ops.iou_box3d import _box_planes, _box_triangles, box3d_overlap
  from pytorch3d.transforms.rotation_conversions import random_rotation
  from .common_testing import get_random_cuda_device, get_tests_dir, TestCaseMixin
label_desc: Use image node_id 15 for calling the TestIoU3D obj's underlying member method code with example usage: obj.iou(N, M, device) and returns: output