code: def _assert_compare_with_expected(
      self,
      model: Module,
      target_layer: Module,
      test_input: Union[Tensor, Tuple[Tensor, ...]],
      expected_ig: Tuple[List[List[float]], ...],
      additional_input: Any = None,
  ):
      layer_ig = LayerIntegratedGradients(model, target_layer)
      attributions = layer_ig.attribute(
          test_input, target=0, additional_forward_args=additional_input
      )
      assertTensorTuplesAlmostEqual(
          self, attributions, expected_ig, delta=0.01
      )
  
imports: from typing import Any, cast, List, Tuple, Union
  import torch
  from captum.attr._core.integrated_gradients import IntegratedGradients
  from captum.attr._core.layer.layer_activation import LayerActivation
  from captum.attr._core.layer.layer_conductance import LayerConductance
  from captum.attr._core.layer.layer_integrated_gradients import LayerIntegratedGradients
  from captum.attr._models.base import configure_interpretable_embedding_layer, remove_interpretable_embedding_layer
  from tests.helpers.basic import assertTensorAlmostEqual, assertTensorTuplesAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicEmbeddingModel, BasicModel_MultiLayer, BasicModel_MultiLayer_TrueMultiInput
  from torch import Tensor
  from torch.nn import Module
label_desc: Use image node_id 13 for calling the Test obj's underlying member method code with example usage: obj._assert_compare_with_expected(model, target_layer, test_input, expected_ig, additional_input) without return types