code: def _layer_activation_test_assert(
      self,
      model: Module,
      target_layer: ModuleOrModuleList,
      test_input: Union[Tensor, Tuple[Tensor, ...]],
      expected_activation: Union[List, Tuple[List[List[float]], ...]],
      additional_input: Any = None,
  ) -> None:
      layer_act = LayerGradientXActivation(model, target_layer)
      self.assertTrue(layer_act.multiplies_by_inputs)
      attributions = layer_act.attribute(
          test_input, target=0, additional_forward_args=additional_input
      )
      if isinstance(target_layer, Module):
          assertTensorTuplesAlmostEqual(
              self, attributions, expected_activation, delta=0.01
          )
      else:
          for i in range(len(target_layer)):
              assertTensorTuplesAlmostEqual(
                  self,
                  attributions[i],
                  expected_activation[i],
                  delta=0.01,
              )
      # test Layer Gradient without multiplying with activations
      layer_grads = LayerGradientXActivation(
          model, target_layer, multiply_by_inputs=False
      )
      layer_act = LayerActivation(model, target_layer)
      self.assertFalse(layer_grads.multiplies_by_inputs)
      grads = layer_grads.attribute(
          test_input, target=0, additional_forward_args=additional_input
      )
      acts = layer_act.attribute(
          test_input, additional_forward_args=additional_input
      )
      if isinstance(target_layer, Module):
          assertTensorTuplesAlmostEqual(
              self,
              attributions,
              tuple(act * grad for act, grad in zip(acts, grads)),
              delta=0.01,
          )
      else:
          for i in range(len(target_layer)):
              assertTensorTuplesAlmostEqual(
                  self,
                  attributions[i],
                  tuple(
                      act * grad for act, grad in zip(acts[i], grads[i])
                  ),
                  delta=0.01,
              )
  
imports: import unittest
  from typing import Any, List, Tuple, Union
  import torch
  from captum._utils.typing import ModuleOrModuleList
  from captum.attr._core.layer.layer_activation import LayerActivation
  from captum.attr._core.layer.layer_gradient_x_activation import LayerGradientXActivation
  from tests.helpers.basic import assertTensorTuplesAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicEmbeddingModel, 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._layer_activation_test_assert(model, target_layer, test_input, expected_activation, additional_input) without return types