code: def test_smoke(self, input_depth, guidance_depth, device, dtype):
      b, h, w = 2, 8, 15
      kernel_size = 5
      sigma_color = 0.1
      sigma_space = (2, 2)
      inp = torch.rand(b, input_depth, h, w, device=device, dtype=dtype)
      guide = torch.rand(
          b, guidance_depth, h, w, device=device, dtype=dtype
      )
  
      out = joint_bilateral_blur(
          inp, guide, kernel_size, sigma_color, sigma_space
      )
      assert isinstance(out, torch.Tensor)
      assert out.shape == (b, input_depth, h, w)
  
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 1 for calling the TestJointBilateralBlur obj's underlying member method code with example usage: obj.test_smoke(input_depth, guidance_depth, device, dtype) without return types