code: def test_lrp_simple_inplaceReLU(self) -> None:
      model_default, inputs = _get_simple_model()
      model_inplace, _ = _get_simple_model(inplace=True)
      for model in [model_default, model_inplace]:
          model.eval()
          model.linear.rule = EpsilonRule()
          model.linear2.rule = EpsilonRule()
      lrp_default = LayerLRP(model_default, model_default.linear2)
      lrp_inplace = LayerLRP(model_inplace, model_inplace.linear2)
      relevance_default = lrp_default.attribute(
          inputs, attribute_to_layer_input=True
      )
      relevance_inplace = lrp_inplace.attribute(
          inputs, attribute_to_layer_input=True
      )
      assertTensorAlmostEqual(
          self, relevance_default[0], relevance_inplace[0]
      )
  
imports: import torch
  import torch.nn
  from captum.attr import LayerLRP
  from captum.attr._utils.lrp_rules import Alpha1_Beta0_Rule, EpsilonRule, GammaRule
  from ...helpers.basic import assertTensorAlmostEqual, BaseTest
  from ...helpers.basic_models import BasicModel_ConvNet_One_Conv, SimpleLRPModel
label_desc: Use image node_id 6 for calling the Test obj's underlying member method code with example usage: obj.test_lrp_simple_inplaceReLU() without return types