code: def test_smoke(self, batch_size, device, dtype):
      src, dst = _sample_points(batch_size, device)
      tensor = torch.rand(batch_size, 3, 32, 32, device=device)
      kernel, affine = kornia.geometry.transform.get_tps_transform(
          src, dst
      )
      warp = kornia.geometry.transform.warp_image_tps(
          tensor, dst, kernel, affine
      )
      assert warp.shape == tensor.shape
  
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 1 for calling the TestWarpImage obj's underlying member method code with example usage: obj.test_smoke(batch_size, device, dtype) without return types