code: def test_cardinality(self, shape, kernel_size, device, dtype):
      sigma = (1.5, 2.1)
      sample = torch.rand(shape, device=device, dtype=dtype)
      actual = gaussian_blur2d(sample, kernel_size, sigma, "replicate")
      assert actual.shape == shape
  
imports: import pytest
  import torch
  from kornia.filters import GaussianBlur2d, gaussian_blur2d, get_gaussian_discrete_kernel1d, get_gaussian_erf_kernel1d, get_gaussian_kernel1d, get_gaussian_kernel2d, get_gaussian_kernel3d
  from kornia.testing import BaseTester, assert_close, tensor_to_gradcheck_var
label_desc: Use image node_id 2 for calling the TestGaussianBlur2d obj's underlying member method code with example usage: obj.test_cardinality(shape, kernel_size, device, dtype) without return types