code: def _internal_influence_test_assert(
      self,
      model: Module,
      target_layer: Module,
      test_input: Union[Tensor, Tuple[Tensor, ...]],
      expected_activation: Union[
          float,
          List[List[float]],
          Tuple[List[float], ...],
          Tuple[List[List[float]], ...],
      ],
      baseline: BaselineType = None,
      additional_args: Any = None,
      attribute_to_layer_input: bool = False,
  ):
      for internal_batch_size in [None, 5, 20]:
          int_inf = InternalInfluence(model, target_layer)
          self.assertFalse(int_inf.multiplies_by_inputs)
          attributions = int_inf.attribute(
              test_input,
              baselines=baseline,
              target=0,
              n_steps=500,
              method="riemann_trapezoid",
              additional_forward_args=additional_args,
              internal_batch_size=internal_batch_size,
              attribute_to_layer_input=attribute_to_layer_input,
          )
          assertTensorTuplesAlmostEqual(
              self,
              attributions,
              expected_activation,
              delta=0.01,
              mode="max",
          )
  
imports: import unittest
  from typing import Any, List, Tuple, Union
  import torch
  from captum._utils.typing import BaselineType
  from captum.attr._core.layer.internal_influence import InternalInfluence
  from tests.helpers.basic import assertTensorTuplesAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel_MultiLayer, BasicModel_MultiLayer_MultiInput
  from torch import Tensor
  from torch.nn import Module
label_desc: Use image node_id 14 for calling the Test obj's underlying member method code with example usage: obj._internal_influence_test_assert(model, target_layer, test_input, expected_activation, baseline, additional_args, attribute_to_layer_input) without return types