code: def test_noncontiguous(self, device, dtype):
      batch_size = 3
      inp = torch.rand(3, 5, 5, device=device, dtype=dtype).expand(
          batch_size, -1, -1, -1
      )
      guide = torch.rand(3, 5, 5, device=device, dtype=dtype).expand(
          batch_size, -1, -1, -1
      )
  
      actual = joint_bilateral_blur(inp, guide, 3, 1, (1, 1))
      assert actual.is_contiguous()
  
imports: import pytest
  import torch
  from kornia.filters import BilateralBlur, JointBilateralBlur, bilateral_blur, joint_bilateral_blur
  from kornia.testing import BaseTester, tensor_to_gradcheck_var
label_desc: Use image node_id 5 for calling the TestJointBilateralBlur obj's underlying member method code with example usage: obj.test_noncontiguous(device, dtype) without return types