code: def test_gradcheck(self, normalized, device):
      batch_size, channels, height, width = 1, 1, 3, 4
      img = torch.rand(
          batch_size, channels, height, width, device=device
      )
      img = tensor_to_gradcheck_var(img)  # to var
      self.gradcheck(sobel, (img, normalized))
  
imports: import pytest
  import torch
  from kornia.filters import Sobel, SpatialGradient, SpatialGradient3d, sobel, spatial_gradient, spatial_gradient3d
  from kornia.testing import BaseTester, tensor_to_gradcheck_var
label_desc: Use image node_id 6 for calling the TestSobel obj's underlying member method code with example usage: obj.test_gradcheck(normalized, device) without return types