code: def _ablation_test_assert(
      self,
      model: Module,
      layer: Module,
      test_input: TensorOrTupleOfTensorsGeneric,
      expected_ablation: Union[
          TensorLikeList,
          Tuple[TensorLikeList, ...],
          Tuple[Tensor, ...],
      ],
      feature_mask: Union[None, TensorOrTupleOfTensorsGeneric] = None,
      additional_input: Any = None,
      perturbations_per_eval: Tuple[int, ...] = (1,),
      baselines: BaselineType = None,
      neuron_selector: Union[
          int, Tuple[Union[int, slice], ...], Callable
      ] = 0,
      attribute_to_neuron_input: bool = False,
  ) -> None:
      for batch_size in perturbations_per_eval:
          ablation = NeuronFeatureAblation(model, layer)
          self.assertTrue(ablation.multiplies_by_inputs)
          attributions = ablation.attribute(
              test_input,
              neuron_selector=neuron_selector,
              feature_mask=feature_mask,
              additional_forward_args=additional_input,
              baselines=baselines,
              perturbations_per_eval=batch_size,
              attribute_to_neuron_input=attribute_to_neuron_input,
          )
          if isinstance(expected_ablation, tuple):
              for i in range(len(expected_ablation)):
                  assertTensorAlmostEqual(
                      self, attributions[i], expected_ablation[i]
                  )
          else:
              assertTensorAlmostEqual(
                  self, attributions, expected_ablation
              )
  
file_path: captum/tests/attr/neuron/test_neuron_ablation.py
imports: import unittest
  from typing import Any, Callable, Tuple, Union
  import torch
  from captum._utils.typing import BaselineType, TensorLikeList, TensorOrTupleOfTensorsGeneric
  from captum.attr._core.neuron.neuron_feature_ablation import NeuronFeatureAblation
  from tests.helpers.basic import assertTensorAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel_ConvNet_One_Conv, BasicModel_MultiLayer, BasicModel_MultiLayer_MultiInput
  from torch import Tensor
  from torch.nn import Module
label_desc: Use image node_id 9 for calling the Test obj's underlying member method code with example usage: obj._ablation_test_assert(model, layer, test_input, expected_ablation, feature_mask, additional_input, perturbations_per_eval, baselines, neuron_selector, attribute_to_neuron_input) without return types