code: def test_gradcheck(self, device):
      batch_size, channels, height, width = 1, 2, 5, 4
      img = torch.rand(
          batch_size, channels, height, width, device=device
      )
      img = tensor_to_gradcheck_var(img)  # to var
      self.gradcheck(max_blur_pool2d, (img, 3))
  
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 5 for calling the TestMaxBlurPool obj's underlying member method code with example usage: obj.test_gradcheck(device) without return types