code: def test_noncontiguous(self, device, dtype):
      batch_size = 3
      sample = torch.rand(3, 5, 5, device=device, dtype=dtype).expand(
          batch_size, -1, -1, -1
      )
  
      kernel_size = (3, 3)
      sigma = (1.5, 2.1)
      actual = gaussian_blur2d(sample, kernel_size, sigma, "replicate")
      assert actual.is_contiguous()
  
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 4 for calling the TestGaussianBlur2d obj's underlying member method code with example usage: obj.test_noncontiguous(device, dtype) without return types