code: def test_smoke(self, border_type, normalized, padding, device, dtype):
      kernel = torch.rand(1, 3, 3, device=device, dtype=dtype)
      _, height, width = kernel.shape
      sample = torch.ones(1, 1, 7, 8, device=device, dtype=dtype)
      b, c, h, w = sample.shape
  
      actual = filter2d(
          sample, kernel, border_type, normalized, padding
      )
      assert isinstance(actual, torch.Tensor)
      assert actual.shape in {
          (b, c, h, w),
          (b, c, h - height + 1, w - width + 1),
      }
  
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 TestFilter2D obj's underlying member method code with example usage: obj.test_smoke(border_type, normalized, padding, device, dtype) without return types