code: def test_gradcheck(self, device):
      def apply_boxes_method(
          tensor: torch.Tensor, method: str, **kwargs
      ):
          boxes = Boxes(tensor)
          result = getattr(boxes, method)(**kwargs)
          return result.data if isinstance(result, Boxes) else result
  
      t_boxes1 = torch.tensor(
          [[[1.0, 1.0], [3.0, 1.0], [3.0, 2.0], [1.0, 2.0]]],
          device=device,
      )
  
      t_boxes1 = tensor_to_gradcheck_var(t_boxes1)
      t_boxes2 = tensor_to_gradcheck_var(t_boxes1.detach().clone())
      t_boxes3 = tensor_to_gradcheck_var(t_boxes1.detach().clone())
      t_boxes4 = tensor_to_gradcheck_var(t_boxes1.detach().clone())
      t_boxes_xyxy = tensor_to_gradcheck_var(
          torch.tensor([[1.0, 3.0, 5.0, 6.0]])
      )
      t_boxes_xyxy1 = tensor_to_gradcheck_var(
          t_boxes_xyxy.detach().clone()
      )
  
      gradcheck(
          partial(apply_boxes_method, method="to_tensor"), (t_boxes2,)
      )
      gradcheck(
          partial(
              apply_boxes_method, method="to_tensor", mode="xyxy_plus"
          ),
          (t_boxes3,),
      )
      gradcheck(
          partial(
              apply_boxes_method,
              method="to_tensor",
              mode="vertices_plus",
          ),
          (t_boxes4,),
      )
      gradcheck(
          partial(apply_boxes_method, method="get_boxes_shape"),
          (t_boxes1,),
      )
      gradcheck(
          lambda x: Boxes.from_tensor(x, mode="xyxy_plus").data,
          (t_boxes_xyxy,),
      )
      gradcheck(
          lambda x: Boxes.from_tensor(x, mode="xywh").data,
          (t_boxes_xyxy1,),
      )
  
imports: from functools import partial
  import pytest
  import torch
  from kornia.geometry.boxes import Boxes, Boxes3D
  from kornia.testing import assert_close, gradcheck, tensor_to_gradcheck_var
label_desc: Use image node_id 10 for calling the TestBoxes2D obj's underlying member method code with example usage: obj.test_gradcheck(device) and returns: unknown