code: def test_relu_deeplift(self) -> None:
      x1 = torch.tensor([1.0], requires_grad=True)
      x2 = torch.tensor([2.0], requires_grad=True)
  
      b1 = torch.tensor([0.0], requires_grad=True)
      b2 = torch.tensor([0.0], requires_grad=True)
  
      inputs = (x1, x2)
      baselines = (b1, b2)
  
      model = ReLUDeepLiftModel()
      self._deeplift_assert(model, DeepLift(model), inputs, baselines)
  
imports: from inspect import signature
  from typing import Callable, List, Tuple, Union
  import torch
  from captum.attr._core.deep_lift import DeepLift, DeepLiftShap
  from captum.attr._core.integrated_gradients import IntegratedGradients
  from tests.helpers.basic import assertAttributionComparision, assertTensorAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModelWithReusedModules, Conv1dSeqModel, LinearMaxPoolLinearModel, ReLUDeepLiftModel, ReLULinearModel, TanhDeepLiftModel
  from torch import Tensor
  from torch.nn import Module
label_desc: Use image node_id 1 for calling the Test obj's underlying member method code with example usage: obj.test_relu_deeplift() without return types