code: def test_lrp_multi(self) -> None:
      model = BasicModel_MultiLayer()
      input = torch.Tensor([[1, 2, 3]])
      add_input = 0
      output = model(input)
      output_add = model(input, add_input=add_input)
      self.assertTrue(torch.equal(output, output_add))
      lrp = LRP(model)
      attributions = lrp.attribute(input, target=0)
      attributions_add_input = lrp.attribute(
          input, target=0, additional_forward_args=(add_input,)
      )
      self.assertTrue(
          torch.equal(attributions, attributions_add_input)  # type: ignore
      )
  
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 17 for calling the Test obj's underlying member method code with example usage: obj.test_lrp_multi() without return types