code: def test_matching_relu2_multi_input_conductance(self) -> None:
      net = BasicModel_ConvNet()
      inp = 100 * torch.randn(3, 1, 10, 10, requires_grad=True)
      baseline = 20 * torch.randn(3, 1, 10, 10, requires_grad=True)
      self._conductance_input_sum_test_assert(
          net, net.relu2, inp, baseline
      )
  
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 11 for calling the Test obj's underlying member method code with example usage: obj.test_matching_relu2_multi_input_conductance() without return types