code: def test_dynamo(self, device, dtype, torch_optimizer):
      # Define script
      op = kornia.geometry.transform.crop_and_resize3d
      op_script = torch_optimizer(op)
  
      img = torch.arange(0.0, 64.0, device=device, dtype=dtype).view(
          1, 1, 4, 4, 4
      )
  
      boxes = torch.tensor(
          [
              [
                  [0, 0, 1],
                  [3, 0, 1],
                  [3, 2, 1],
                  [0, 2, 1],
                  [0, 0, 3],
                  [3, 0, 3],
                  [3, 2, 3],
                  [0, 2, 3],
              ]
          ],
          device=device,
          dtype=dtype,
      )  # 1x8x3
  
      actual = op_script(img, boxes, (4, 3, 2))
      expected = op(img, boxes, (4, 3, 2))
      assert_close(actual, expected)
  
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.testing import assert_close
  from kornia.utils._compat import torch_version
label_desc: Use image node_id 4 for calling the TestCropAndResize3D obj's underlying member method code with example usage: obj.test_dynamo(device, dtype, torch_optimizer) without return types