code: def layer_method_with_input_layer_patches(
      self,
      layer_method_class: Callable,
      equiv_method_class: Callable,
      multi_layer: bool,
  ) -> None:
      model = (
          BasicModel_MultiLayer_TrueMultiInput()
          if multi_layer
          else BasicModel()
      )
  
      input_names = (
          ["x1", "x2", "x3", "x4"] if multi_layer else ["input"]
      )
      model = ModelInputWrapper(model)
  
      layers = [model.input_maps[inp] for inp in input_names]
      layer_method = layer_method_class(
          model, layer=layers if multi_layer else layers[0]
      )
      equivalent_method = equiv_method_class(model)
  
      inputs = tuple(torch.rand(5, 3) for _ in input_names)
      baseline = tuple(torch.zeros(5, 3) for _ in input_names)
  
      args = inspect.getfullargspec(
          equivalent_method.attribute.__wrapped__
      ).args
  
      args_to_use = [inputs]
      if "baselines" in args:
          args_to_use += [baseline]
  
      a1 = layer_method.attribute(*args_to_use, target=0)
      a2 = layer_method.attribute(
          *args_to_use, target=0, attribute_to_layer_input=True
      )
  
      real_attributions = equivalent_method.attribute(
          *args_to_use, target=0
      )
  
      if not isinstance(a1, tuple):
          a1 = (a1,)
          a2 = (a2,)
  
      if not isinstance(real_attributions, tuple):
          real_attributions = (real_attributions,)
  
      assertTensorTuplesAlmostEqual(self, a1, a2)
      assertTensorTuplesAlmostEqual(self, a1, real_attributions)
  
file_path: captum/tests/attr/test_input_layer_wrapper.py
imports: import functools
  import inspect
  from typing import Callable, Dict, Tuple
  import torch
  from captum._utils.gradient import _forward_layer_eval
  from captum.attr import DeepLift, DeepLiftShap, FeatureAblation, GradientShap, InputXGradient, IntegratedGradients, LayerDeepLift, LayerDeepLiftShap, LayerFeatureAblation, LayerGradientShap, LayerGradientXActivation, LayerIntegratedGradients
  from captum.attr._utils.input_layer_wrapper import ModelInputWrapper
  from tests.helpers.basic import assertTensorTuplesAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel, BasicModel_MultiLayer_TrueMultiInput, MixedKwargsAndArgsModule
label_desc: Use image node_id 2 for calling the TestInputLayerWrapper obj's underlying member method code with example usage: obj.layer_method_with_input_layer_patches(layer_method_class, equiv_method_class, multi_layer) without return types