code: def test_smoke(self, device, dtype):
      img = torch.rand(2, 3, 32, 32, device=device, dtype=dtype)
      net = DexiNed(pretrained=False).to(device, dtype)
      out = net(img)
      assert len(out) == 7
      assert out[-1].shape == (2, 1, 32, 32)
  
imports: import pytest
  import torch
  from kornia.filters import DexiNed, filter2d, filter2d_separable, filter3d
  from kornia.testing import BaseTester, assert_close, tensor_to_gradcheck_var
  from kornia.utils._compat import torch_version_le
label_desc: Use image node_id 1 for calling the TestDexiNed obj's underlying member method code with example usage: obj.test_smoke(device, dtype) without return types