code: def test_simple_input_conv_neuron_gb(self) -> None:
      net = BasicModel_ConvNet_One_Conv()
      inp = 1.0 * torch.arange(16, dtype=torch.float).view(1, 1, 4, 4)
      exp = [
          [
              [
                  [0.0, 1.0, 1.0, 1.0],
                  [1.0, 3.0, 3.0, 2.0],
                  [1.0, 3.0, 3.0, 2.0],
                  [1.0, 2.0, 2.0, 1.0],
              ]
          ]
      ]
      self._neuron_guided_backprop_test_assert(
          net, net.fc1, (0,), (inp,), (exp,)
      )
  
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 2 for calling the Test obj's underlying member method code with example usage: obj.test_simple_input_conv_neuron_gb() without return types