code: def test_jit(self, device, dtype):
      B, C, H, W = 1, 1, 32, 32
      patches = torch.rand(B, C, H, W, device=device, dtype=dtype)
      patches2x = resize(patches, (48, 48))
      sample = {"image0": patches, "image1": patches2x}
      model = LoFTR().to(patches.device, patches.dtype).eval()
      model_jit = torch.jit.script(model)
      out = model(sample)
      out_jit = model_jit(sample)
      for k, v in out.items():
          assert_close(v, out_jit[k])
  
file_path: kornia/test/feature/test_loftr.py
imports: import sys
  import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia.testing
  from kornia.feature import LoFTR
  from kornia.geometry import resize
  from kornia.testing import assert_close
  from kornia.utils._compat import torch_version_ge
label_desc: Use image node_id 7 for calling the TestLoFTR obj's underlying member method code with example usage: obj.test_jit(device, dtype) without return types