code: def test_sample_grads_modified_conv_sum(self) -> None:
      if version.parse(torch.__version__) < version.parse("1.8.0"):
          raise unittest.SkipTest(
              "Skipping sample gradient test with 3D linear module"
              "since torch version < 1.8"
          )
  
      model = BasicModel_ConvNetWithPaddingDilation()
      inp = (20 * torch.randn(6, 1, 5, 5),)
      self._compare_sample_grads_per_sample(
          model, inp, lambda x: torch.sum(x), "sum"
      )
  
file_path: captum/tests/utils/test_sample_gradient.py
imports: import unittest
  from typing import Callable, Tuple
  import torch
  from captum._utils.gradient import apply_gradient_requirements
  from captum._utils.sample_gradient import _reset_sample_grads, SampleGradientWrapper, SUPPORTED_MODULES
  from packaging import version
  from tests.helpers.basic import assertTensorAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel_ConvNet_One_Conv, BasicModel_ConvNetWithPaddingDilation, BasicModel_MultiLayer
  from torch import Tensor
  from torch.nn import Module
label_desc: Use image node_id 6 for calling the Test obj's underlying member method code with example usage: obj.test_sample_grads_modified_conv_sum() without return types