code: def test_smoke(self, kernel_size, stride, device, dtype):
      inpt = torch.rand(1, 1, 10, 10, device=device, dtype=dtype)
      actual = BlurPool2D(kernel_size, stride=stride)(inpt)
      expected = (1, 1, int(10 / stride), int(10 / stride))
      assert actual.shape == expected
  
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 TestBlurPool obj's underlying member method code with example usage: obj.test_smoke(kernel_size, stride, device, dtype) without return types