code: def test_gradcheck(self, batch_size, device, dtype):
      # prepare data
      channels, height, width = 3, 3, 5  # output shape
      pinhole_src, pinhole_dst = self._create_pinhole_pair(
          batch_size, device, dtype
      )
  
      # initialize depth to one
      depth_src = torch.ones(
          batch_size, 1, height, width, device=device, dtype=dtype
      )
      depth_src = utils.tensor_to_gradcheck_var(depth_src)  # to var
  
      # create patch to warp
      img_dst = torch.ones(
          batch_size,
          channels,
          height,
          width,
          device=device,
          dtype=dtype,
      )
      img_dst = utils.tensor_to_gradcheck_var(img_dst)  # to var
  
      # evaluate function gradient
      assert gradcheck(
          kornia.geometry.depth.depth_warp,
          (pinhole_dst, pinhole_src, depth_src, img_dst, height, width),
          raise_exception=True,
          fast_mode=True,
      )
  
file_path: kornia/test/geometry/test_depth_warper.py
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.geometry.conversions import normalize_pixel_coordinates
  from kornia.testing import assert_close
label_desc: Use image node_id 8 for calling the TestDepthWarper obj's underlying member method code with example usage: obj.test_gradcheck(batch_size, device, dtype) without return types