code: def test_smoke(self, device, dtype):
      # Sample two points of the 3d rect
      points = torch.rand(1, 6, device=device, dtype=dtype)
  
      # Fill according missing points
      bbox = torch.zeros(1, 8, 3, device=device, dtype=dtype)
      bbox[0, 0] = points[0][:3]
      bbox[0, 1, 0] = points[0][3]
      bbox[0, 1, 1] = points[0][1]
      bbox[0, 1, 2] = points[0][2]
      bbox[0, 2, 0] = points[0][3]
      bbox[0, 2, 1] = points[0][4]
      bbox[0, 2, 2] = points[0][2]
      bbox[0, 3, 0] = points[0][0]
      bbox[0, 3, 1] = points[0][4]
      bbox[0, 3, 2] = points[0][2]
      bbox[0, 4, 0] = points[0][0]
      bbox[0, 4, 1] = points[0][1]
      bbox[0, 4, 2] = points[0][5]
      bbox[0, 5, 0] = points[0][3]
      bbox[0, 5, 1] = points[0][1]
      bbox[0, 5, 2] = points[0][5]
      bbox[0, 6] = points[0][3:]
      bbox[0, 7, 0] = points[0][0]
      bbox[0, 7, 1] = points[0][4]
      bbox[0, 7, 2] = points[0][5]
  
      # Validate
      assert validate_bbox3d(bbox)
  
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 1 for calling the TestBbox3D obj's underlying member method code with example usage: obj.test_smoke(device, dtype) without return types