code: def test_dynamo(self, device, dtype, torch_optimizer):
      if (
          dtype == torch.float64
          and torch_version() in {"2.0.0", "2.0.1"}
          and sys.platform == "linux"
      ):
          pytest.xfail(
              "Failing on CI on ubuntu with torch 2.0.0 for float64"
          )
      img = torch.rand(1, 2, 3, 4, device=device, dtype=dtype)
      H_ab = kornia.eye_like(3, img)
      args = (img, H_ab, (4, 5))
      op = kornia.geometry.warp_perspective
      op_optimized = torch_optimizer(op)
      assert_close(op(*args), op_optimized(*args))
  
imports: import sys
  import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.testing import assert_close
  from kornia.utils._compat import torch_version, torch_version_lt
  from kornia.utils.helpers import _torch_inverse_cast
label_desc: Use image node_id 9 for calling the TestWarpPerspective obj's underlying member method code with example usage: obj.test_dynamo(device, dtype, torch_optimizer) without return types