code: def test_linear_neuron_deeplift_shap(self) -> None:
      model = ReLULinearModel()
      (
          inputs,
          baselines,
      ) = _create_inps_and_base_for_deepliftshap_neuron_layer_testing()
  
      neuron_dl = NeuronDeepLiftShap(model, model.l3)
      attributions = neuron_dl.attribute(
          inputs, 0, baselines, attribute_to_neuron_input=True
      )
      assertTensorAlmostEqual(
          self, attributions[0], [[-0.0, 0.0, -0.0]]
      )
      assertTensorAlmostEqual(self, attributions[1], [[0.0, 0.0, 0.0]])
  
      attributions = neuron_dl.attribute(
          inputs, 0, baselines, attribute_to_neuron_input=False
      )
  
      self.assertTrue(neuron_dl.multiplies_by_inputs)
      assertTensorAlmostEqual(
          self, attributions[0], [[-0.0, 0.0, -0.0]]
      )
      assertTensorAlmostEqual(self, attributions[1], [[6.0, 9.0, 0.0]])
  
imports: from __future__ import print_function
  from typing import Tuple, Union
  import torch
  from captum._utils.typing import TensorOrTupleOfTensorsGeneric
  from captum.attr._core.neuron.neuron_deep_lift import NeuronDeepLift, NeuronDeepLiftShap
  from tests.attr.layer.test_layer_deeplift import _create_inps_and_base_for_deeplift_neuron_layer_testing, _create_inps_and_base_for_deepliftshap_neuron_layer_testing
  from tests.helpers.basic import assertTensorAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel_ConvNet, BasicModel_ConvNet_MaxPool3d, LinearMaxPoolLinearModel, ReLULinearModel
  from torch import Tensor
label_desc: Use image node_id 7 for calling the Test obj's underlying member method code with example usage: obj.test_linear_neuron_deeplift_shap() without return types