code: def test_simple_multi_input_conv(self) -> None:
      net = BasicModel_ConvNet_One_Conv()
      inp = torch.arange(16, dtype=torch.float).view(1, 1, 4, 4)
      inp2 = torch.ones((1, 1, 4, 4))
      self._occlusion_test_assert(
          net,
          (inp, inp2),
          (67 * torch.ones_like(inp), 13 * torch.ones_like(inp2)),
          perturbations_per_eval=(1, 2, 4, 8, 12, 16),
          sliding_window_shapes=((1, 4, 4), (1, 4, 4)),
      )
      self._occlusion_test_assert(
          net,
          (inp, inp2),
          (
              [
                  [
                      [
                          [17.0, 17.0, 17.0, 17.0],
                          [17.0, 17.0, 17.0, 17.0],
                          [64.0, 65.5, 65.5, 67.0],
                          [64.0, 65.5, 65.5, 67.0],
                      ]
                  ]
              ],
              [
                  [
                      [
                          [3.0, 3.0, 3.0, 3.0],
                          [3.0, 3.0, 3.0, 3.0],
                          [3.0, 3.0, 3.0, 3.0],
                          [0.0, 0.0, 0.0, 0.0],
                      ]
                  ]
              ],
          ),
          perturbations_per_eval=(1, 3, 7, 14),
          sliding_window_shapes=((1, 2, 3), (1, 1, 2)),
          strides=((1, 2, 1), (1, 1, 2)),
      )
  
imports: import io
  import unittest
  import unittest.mock
  from typing import Any, Callable, Tuple, Union
  import torch
  from captum._utils.typing import BaselineType, TargetType, TensorLikeList, TensorOrTupleOfTensorsGeneric
  from captum.attr._core.occlusion import Occlusion
  from tests.helpers.basic import assertTensorAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel3, BasicModel_ConvNet_One_Conv, BasicModel_MultiLayer, BasicModel_MultiLayer_MultiInput
  from torch import Tensor
label_desc: Use image node_id 14 for calling the Test obj's underlying member method code with example usage: obj.test_simple_multi_input_conv() without return types