code: def test_gradcheck(self, device):
      batch_size, channels, height, width = 1, 2, 5, 4
      img = torch.rand(
          batch_size, channels, height, width, device=device
      )
      img = utils.tensor_to_gradcheck_var(img)  # to var
      assert gradcheck(
          kornia.feature.gftt_response,
          (img),
          raise_exception=True,
          nondet_tol=1e-4,
          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 TestCornerGFTT obj's underlying member method code with example usage: obj.test_gradcheck(device) without return types