code: def test_jit(self, device, dtype):
      op = gradient
      op_script = torch.jit.script(op)
  
      tensor = torch.rand(1, 2, 7, 7, device=device, dtype=dtype)
      kernel = torch.ones(3, 3, device=device, dtype=dtype)
  
      actual = op_script(tensor, kernel)
      expected = op(tensor, kernel)
  
      assert_close(actual, expected)
  
file_path: kornia/test/morphology/test_gradient.py
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  from kornia.morphology import gradient
  from kornia.testing import assert_close
label_desc: Use image node_id 7 for calling the TestGradient obj's underlying member method code with example usage: obj.test_jit(device, dtype) without return types