code: def test_simple_input_conv_split_channels(self) -> None:
      net = BasicModel_ConvNet_One_Conv()
      inp = torch.arange(16).view(1, 1, 4, 4).float()
      expected_result = [
          [
              [[-3.7500, 3.0000], [23.2500, 30.0000]],
              [[15.0000, 10.5000], [-3.0000, -7.5000]],
          ]
      ]
      self._grad_cam_test_assert(
          net,
          net.conv1,
          inp,
          expected_activation=expected_result,
          attr_dim_summation=False,
      )
  
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 4 for calling the Test obj's underlying member method code with example usage: obj.test_simple_input_conv_split_channels() without return types