code: def test_lrp_maxpool2D(self) -> None:
      class MaxPoolModel(nn.Module):
          def __init__(self) -> None:
              super().__init__()
              self.maxpool = nn.MaxPool2d(2)
  
          def forward(self, input: Tensor) -> Module:
              return self.maxpool(input)
  
      model = MaxPoolModel()
      input = torch.tensor([[[[1.0, 2.0], [5.0, 6.0]]]])
      lrp = LRP(model)
      relevance = lrp.attribute(input)
      assertTensorAlmostEqual(
          self, relevance, torch.Tensor([[[[0.0, 0.0], [0.0, 6.0]]]])
      )
  
imports: from typing import cast, Tuple
  import torch
  import torch.nn
  from captum.attr import InputXGradient, LRP
  from captum.attr._utils.lrp_rules import Alpha1_Beta0_Rule, EpsilonRule, GammaRule, IdentityRule
  from tests.helpers.basic import assertTensorAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel_ConvNet_One_Conv, BasicModel_MultiLayer, BasicModelWithReusedLinear, SimpleLRPModel
  from torch import Tensor
  from torch.nn import Module
label_desc: Use image node_id 15 for calling the Test obj's underlying member method code with example usage: obj.test_lrp_maxpool2D() and returns: self