code: def test_lrp_maxpool1D(self) -> None:
      class MaxPoolModel(nn.Module):
          def __init__(self) -> None:
              super().__init__()
              self.linear = nn.Linear(2, 2, bias=False)
              self.linear.weight.data.fill_(2.0)
              self.maxpool = nn.MaxPool1d(2)
  
          def forward(self, input: Tensor) -> Module:
              return self.maxpool(self.linear(input))
  
      model = MaxPoolModel()
      input = torch.tensor([[[1.0, 2.0], [5.0, 6.0]]])
      lrp = LRP(model)
      relevance = lrp.attribute(input, target=1)
      assertTensorAlmostEqual(
          self, relevance, torch.Tensor([[[0.0, 0.0], [10, 12]]])
      )
  
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 14 for calling the Test obj's underlying member method code with example usage: obj.test_lrp_maxpool1D() and returns: self