code: def test_gradcheck(self, device):
      # test parameters
      batch_shape = (1, 2, 5, 7)
      kernel_size = 3
  
      # evaluate function gradient
      sample = torch.rand(batch_shape, device=device)
      sample = tensor_to_gradcheck_var(sample)
      self.gradcheck(laplacian, (sample, kernel_size))
  
file_path: kornia/test/filters/test_laplacian.py
imports: import pytest
  import torch
  from kornia.filters import Laplacian, get_laplacian_kernel1d, get_laplacian_kernel2d, laplacian
  from kornia.testing import BaseTester, assert_close, tensor_to_gradcheck_var
label_desc: Use image node_id 5 for calling the TestLaplacian obj's underlying member method code with example usage: obj.test_gradcheck(device) without return types