code: def test_basic_multilayer_with_add_args(self) -> None:
      model = BasicModel_MultiLayer(inplace=True)
      model.eval()
  
      inputs = torch.tensor([[1.0, -20.0, 10.0]])
      add_args = torch.ones(1, 3)
      baselines = torch.randn(30, 3)
      expected = [[-13.9510, 0.0]]
  
      self._assert_attributions(
          model,
          model.linear2,
          inputs,
          baselines,
          0,
          expected,
          add_args=add_args,
      )
  
imports: from typing import Any, Callable, List, Tuple, Union
  import torch
  from captum._utils.typing import TargetType, TensorOrTupleOfTensorsGeneric
  from captum.attr._core.gradient_shap import GradientShap
  from captum.attr._core.layer.layer_gradient_shap import LayerGradientShap
  from tests.attr.test_gradient_shap import _assert_attribution_delta
  from tests.helpers.basic import assertTensorAlmostEqual, assertTensorTuplesAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel_MultiLayer, BasicModel_MultiLayer_MultiInput
  from tests.helpers.classification_models import SoftmaxModel
  from torch import Tensor
  from torch.nn import Module
label_desc: Use image node_id 4 for calling the Test obj's underlying member method code with example usage: obj.test_basic_multilayer_with_add_args() without return types