code: def test_gradcheck(self, device, dtype):
      img = torch.rand(1, 2, 5, 4, device=device, dtype=dtype)
      img = utils.tensor_to_gradcheck_var(img)  # to var
  
      boxes = torch.tensor(
          [[[1.0, 1.0], [2.0, 1.0], [2.0, 2.0], [1.0, 2.0]]],
          device=device,
          dtype=dtype,
      )  # 1x4x2
      boxes = utils.tensor_to_gradcheck_var(
          boxes, requires_grad=False
      )  # to var
  
      assert gradcheck(
          kornia.geometry.transform.crop_and_resize,
          (img, boxes, (4, 2)),
          raise_exception=True,
          fast_mode=True,
      )
  
imports: import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.testing import assert_close
label_desc: Use image node_id 5 for calling the TestCropAndResize obj's underlying member method code with example usage: obj.test_gradcheck(device, dtype) without return types