code: def test_gradcheck(self, device):
      # generate input data
      disparity = torch.rand(1, 1, 3, 4, device=device)
      disparity = utils.tensor_to_gradcheck_var(disparity)  # to var
  
      baseline = torch.rand(1, device=device)
      baseline = utils.tensor_to_gradcheck_var(baseline)  # to var
  
      focal = torch.rand(1, device=device)
      focal = utils.tensor_to_gradcheck_var(focal)  # to var
  
      # evaluate function gradient
      assert gradcheck(
          kornia.geometry.depth.depth_from_disparity,
          (disparity, baseline, focal),
          raise_exception=True,
          fast_mode=True,
      )
  
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.testing import assert_close
label_desc: Use image node_id 4 for calling the TestDepthFromDisparity obj's underlying member method code with example usage: obj.test_gradcheck(device) without return types