code: def test_dynamo(self, batch_size, device, dtype, torch_optimizer):
      if dtype == torch.float64:
          # TODO: investigate sobel for float64 with dynamo
          pytest.xfail(
              reason="The sobel results can be different after dynamo on fp64"
          )
      inpt = torch.ones(
          batch_size, 3, 10, 10, device=device, dtype=dtype
      )
      op = Sobel()
      op_optimized = torch_optimizer(op)
  
      self.assert_close(op(inpt), op_optimized(inpt))
  
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 8 for calling the TestSobel obj's underlying member method code with example usage: obj.test_dynamo(batch_size, device, dtype, torch_optimizer) without return types