code: def test_gradcheck(self, device):
      points_src = utils.tensor_to_gradcheck_var(
          torch.rand(
              1,
              10,
              2,
              device=device,
              dtype=torch.float64,
              requires_grad=True,
          )
      )
      points_dst = utils.tensor_to_gradcheck_var(
          torch.rand_like(points_src)
      )
      weights = utils.tensor_to_gradcheck_var(
          torch.ones_like(points_src)[..., 0]
      )
  
      assert gradcheck(
          find_homography_dlt,
          (points_src, points_dst, weights),
          rtol=1e-6,
          atol=1e-6,
          raise_exception=True,
          fast_mode=True,
      )
  
imports: import sys
  import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.geometry.homography import find_homography_dlt, find_homography_dlt_iterated, find_homography_lines_dlt, find_homography_lines_dlt_iterated, line_segment_transfer_error_one_way, oneway_transfer_error, sample_is_valid_for_homography, symmetric_transfer_error
  from kornia.testing import assert_close
  from kornia.utils._compat import torch_version_le
label_desc: Use image node_id 9 for calling the TestFindHomographyDLT obj's underlying member method code with example usage: obj.test_gradcheck(device) without return types