code: def _conductance_input_sum_test_assert(
      self,
      model: Module,
      target_layer: Module,
      test_input: TensorOrTupleOfTensorsGeneric,
      test_baseline: BaselineType = None,
  ):
      layer_cond = LayerConductance(model, target_layer)
      attributions = cast(
          Tensor,
          layer_cond.attribute(
              test_input,
              baselines=test_baseline,
              target=0,
              n_steps=500,
              method="gausslegendre",
          ),
      )
      neuron_cond = NeuronConductance(model, target_layer)
      attr_shape = cast(Tuple[int, ...], attributions.shape)
      for i in range(attr_shape[1]):
          for j in range(attr_shape[2]):
              for k in range(attr_shape[3]):
                  neuron_vals = neuron_cond.attribute(
                      test_input,
                      (i, j, k),
                      baselines=test_baseline,
                      target=0,
                      n_steps=500,
                  )
                  for n in range(attributions.shape[0]):
                      self.assertAlmostEqual(
                          torch.sum(neuron_vals[n]).item(),
                          attributions[n, i, j, k].item(),
                          delta=0.005,
                      )
  
imports: import unittest
  from typing import Any, Callable, cast, List, Tuple, Union
  import torch
  from captum._utils.typing import BaselineType, TensorOrTupleOfTensorsGeneric
  from captum.attr._core.layer.layer_conductance import LayerConductance
  from captum.attr._core.neuron.neuron_conductance import NeuronConductance
  from tests.helpers.basic import assertTensorAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel_ConvNet, BasicModel_MultiLayer, BasicModel_MultiLayer_MultiInput
  from torch import Tensor
  from torch.nn import Module
label_desc: Use image node_id 16 for calling the Test obj's underlying member method code with example usage: obj._conductance_input_sum_test_assert(model, target_layer, test_input, test_baseline) without return types