code: def _neuron_guided_backprop_test_assert(
      self,
      model: Module,
      layer: Module,
      neuron_selector: Union[int, Tuple[Union[int, slice], ...]],
      test_input: TensorOrTupleOfTensorsGeneric,
      expected: Tuple[List[List[List[List[float]]]], ...],
      additional_input: Any = None,
  ) -> None:
      guided_backprop = NeuronGuidedBackprop(model, layer)
      attributions = guided_backprop.attribute(
          test_input,
          neuron_selector=neuron_selector,
          additional_forward_args=additional_input,
      )
      for i in range(len(test_input)):
          assertTensorAlmostEqual(
              self,
              attributions[i],
              expected[i],
              delta=0.01,
          )
  
file_path: captum/tests/attr/test_guided_backprop.py
imports: import unittest
  from typing import Any, List, Tuple, Union
  import torch
  from captum._utils.typing import TensorLikeList, TensorOrTupleOfTensorsGeneric
  from captum.attr._core.guided_backprop_deconvnet import GuidedBackprop
  from captum.attr._core.neuron.neuron_guided_backprop_deconvnet import NeuronGuidedBackprop
  from tests.helpers.basic import assertTensorAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel_ConvNet_One_Conv
  from torch.nn import Module
label_desc: Use image node_id 8 for calling the Test obj's underlying member method code with example usage: obj._neuron_guided_backprop_test_assert(model, layer, neuron_selector, test_input, expected, additional_input) without return types