code: def test_lrp_simple_attributions_AlphaBeta(self) -> None:
      model, inputs = _get_simple_model()
      with torch.no_grad():
          model.linear.weight.data[0][0] = -2
      model.eval()
      model.linear.rule = Alpha1_Beta0_Rule()
      model.linear2.rule = Alpha1_Beta0_Rule()
      lrp = LayerLRP(model, model.linear)
      relevance = lrp.attribute(inputs)
      assertTensorAlmostEqual(
          self, relevance[0], torch.tensor([24.0, 36.0, 36.0])
      )
  
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 9 for calling the Test obj's underlying member method code with example usage: obj.test_lrp_simple_attributions_AlphaBeta() without return types