code: def test_bounding_boxes_dim_inferring(self, device, dtype):
      boxes = torch.tensor(
          [
              [
                  [0, 1, 2],
                  [10, 1, 2],
                  [10, 21, 2],
                  [0, 21, 2],
                  [0, 1, 32],
                  [10, 1, 32],
                  [10, 21, 32],
                  [0, 21, 32],
              ],
              [
                  [3, 4, 5],
                  [43, 4, 5],
                  [43, 54, 5],
                  [3, 54, 5],
                  [3, 4, 65],
                  [43, 4, 65],
                  [43, 54, 65],
                  [3, 54, 65],
              ],
          ],
          device=device,
          dtype=dtype,
      )  # 2x8x3
      d, h, w = infer_bbox_shape3d(boxes)
  
      assert_close(
          d, torch.tensor([31.0, 61.0], device=device, dtype=dtype)
      )
      assert_close(
          h, torch.tensor([21.0, 51.0], device=device, dtype=dtype)
      )
      assert_close(
          w, torch.tensor([11.0, 41.0], device=device, dtype=dtype)
      )
  
imports: import torch
  import kornia
  from kornia.geometry.bbox import infer_bbox_shape, infer_bbox_shape3d, nms, transform_bbox, validate_bbox, validate_bbox3d
  from kornia.testing import assert_close, gradcheck, tensor_to_gradcheck_var
label_desc: Use image node_id 2 for calling the TestBbox3D obj's underlying member method code with example usage: obj.test_bounding_boxes_dim_inferring(device, dtype) without return types