code: def test_lrp_simple_attributions_GammaRule(self) -> None:
      model, inputs = _get_simple_model()
      with torch.no_grad():
          model.linear.weight.data[0][0] = -2  # type: ignore
      model.eval()
      model.linear.rule = GammaRule(gamma=1)  # type: ignore
      model.linear2.rule = GammaRule()  # type: ignore
      lrp = LRP(model)
      relevance = lrp.attribute(inputs)
      assertTensorAlmostEqual(
          self, relevance.data, torch.tensor([[28 / 3, 104 / 3, 52]])  # 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 9 for calling the Test obj's underlying member method code with example usage: obj.test_lrp_simple_attributions_GammaRule() without return types