code: def test_relu_deepliftshap_batch_4D_input_wo_mutliplying_by_inputs(
      self,
  ) -> None:
      x1 = torch.ones(4, 1, 1, 1)
      x2 = torch.tensor([[[[2.0]]]] * 4)
  
      b1 = torch.zeros(4, 1, 1, 1)
      b2 = torch.zeros(4, 1, 1, 1)
  
      inputs = (x1, x2)
      baselines = (b1, b2)
  
      model = ReLUDeepLiftModel()
      attr = DeepLiftShap(model, multiply_by_inputs=False).attribute(
          inputs, baselines
      )
      assertTensorAlmostEqual(self, attr[0], 2 * torch.ones(4, 1, 1, 1))
      assertTensorAlmostEqual(
          self, attr[1], 0.5 * torch.ones(4, 1, 1, 1)
      )
  
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 12 for calling the Test obj's underlying member method code with example usage: obj.test_relu_deepliftshap_batch_4D_input_wo_mutliplying_by_inputs() without return types