code: def test_jit(self, batch_size, device, dtype):
      src, dst = _sample_points(batch_size, device)
      kernel, affine = kornia.geometry.transform.get_tps_transform(
          src, dst
      )
      image = torch.rand(batch_size, 3, 32, 32, device=device)
      op = kornia.geometry.transform.warp_image_tps
      op_jit = torch.jit.script(op)
      assert_close(
          op(image, dst, kernel, affine),
          op_jit(image, dst, kernel, affine),
          rtol=1e-4,
          atol=1e-4,
      )
  
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 5 for calling the TestWarpImage obj's underlying member method code with example usage: obj.test_jit(batch_size, device, dtype) without return types