code: def test_cardinality(self, batch_size, padding, device, dtype):
      B: int = batch_size
      kernel = torch.rand(1, 3, 3, device=device, dtype=dtype)
      _, height, width = kernel.shape
      sample = torch.ones(B, 3, 7, 8, device=device, dtype=dtype)
      b, c, h, w = sample.shape
      out = filter2d(sample, kernel, padding=padding)
      if padding == "same":
          assert out.shape == (b, c, h, w)
      else:
          assert out.shape == (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 2 for calling the TestFilter2D obj's underlying member method code with example usage: obj.test_cardinality(batch_size, padding, device, dtype) without return types