code: def test_lrp_basic_attributions(self) -> None:
      model, inputs = _get_basic_config()
      logits = model(inputs)
      _, classIndex = torch.max(logits, 1)
      lrp = LRP(model)
      relevance, delta = lrp.attribute(
          inputs,
          cast(int, classIndex.item()),
          return_convergence_delta=True,
      )
      self.assertEqual(delta.item(), 0)  # type: ignore
      self.assertEqual(relevance.shape, inputs.shape)  # type: ignore
      assertTensorAlmostEqual(
          self,
          relevance,
          torch.Tensor(
              [
                  [
                      [
                          [0, 1, 2, 3],
                          [0, 5, 6, 7],
                          [0, 9, 10, 11],
                          [0, 0, 0, 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 3 for calling the Test obj's underlying member method code with example usage: obj.test_lrp_basic_attributions() without return types