code: def test_simple_input_conv_fc_with_final_relu(self) -> None:
      net = BasicModel_ConvNet_One_Conv()
      inp = torch.arange(16).view(1, 1, 4, 4).float()
      # Adding negative value to test final relu is applied
      inp[0, 0, 1, 1] = -4.0
      inp.requires_grad_()
      exp = 0.5625 * inp
      exp[0, 0, 1, 1] = 0.0
      self._grad_cam_test_assert(
          net,
          net.conv1,
          inp,
          exp,
          attribute_to_layer_input=True,
          relu_attributions=True,
      )
  
imports: import unittest
  from typing import Any, Tuple, Union
  import torch
  from captum._utils.typing import TensorLikeList
  from captum.attr._core.layer.grad_cam import LayerGradCam
  from tests.helpers.basic import assertTensorTuplesAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel_ConvNet_One_Conv, BasicModel_MultiLayer
  from torch import Tensor
  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.test_simple_input_conv_fc_with_final_relu() without return types