code: def test_smoke(self, kernel_size, ceil_mode, device, dtype):
      inpt = torch.rand(1, 1, 10, 10, device=device, dtype=dtype)
      actual = MaxBlurPool2D(kernel_size, ceil_mode=ceil_mode)(inpt)
  
      assert actual.shape == (1, 1, 5, 5)
  
imports: import pytest
  import torch
  from kornia.filters import BlurPool2D, EdgeAwareBlurPool2D, MaxBlurPool2D, blur_pool2d, edge_aware_blur_pool2d, max_blur_pool2d
  from kornia.testing import BaseTester, tensor_to_gradcheck_var
label_desc: Use image node_id 1 for calling the TestMaxBlurPool obj's underlying member method code with example usage: obj.test_smoke(kernel_size, ceil_mode, device, dtype) without return types