code: def test_gradcheck(self, batch_size, device, dtype, requires_grad):
      opts = {"device": device, "dtype": torch.float64}
      src, dst = _sample_points(batch_size, **opts)
      kernel, affine = kornia.geometry.transform.get_tps_transform(
          src, dst
      )
      kernel.requires_grad_(requires_grad)
      affine.requires_grad_(not requires_grad)
      assert gradcheck(
          kornia.geometry.transform.warp_points_tps,
          (src, dst, kernel, affine),
          raise_exception=True,
          fast_mode=True,
      )
  
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia
  from kornia.testing import assert_close
  from kornia.utils._compat import torch_version_ge
label_desc: Use image node_id 4 for calling the TestWarpPoints obj's underlying member method code with example usage: obj.test_gradcheck(batch_size, device, dtype, requires_grad) without return types