code: def test_simple_multi_input_relu_input(self) -> None:
      net = BasicModel_ConvNet_One_Conv(inplace=True)
      inp = torch.arange(16, dtype=torch.float).view(1, 1, 4, 4)
      inp2 = torch.ones((1, 1, 4, 4))
      ex = [
          [
              [
                  [14.5, 29.0, 38.0, 19.0],
                  [29.0, 58.0, 76.0, 38.0],
                  [65.0, 130.0, 148.0, 74.0],
                  [32.5, 65.0, 74.0, 37.0],
              ]
          ]
      ]
      self._guided_grad_cam_test_assert(
          net,
          net.relu1,
          (inp, inp2),
          (ex, ex),
          attribute_to_layer_input=True,
      )
  
file_path: captum/tests/attr/test_guided_grad_cam.py
imports: import unittest
  from typing import Any
  import torch
  from captum._utils.typing import TensorOrTupleOfTensorsGeneric
  from captum.attr._core.guided_grad_cam import GuidedGradCam
  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 3 for calling the Test obj's underlying member method code with example usage: obj.test_simple_multi_input_relu_input() without return types