code: def test_multi_input_ablation_with_baselines(self) -> None:
      net = BasicModel_MultiLayer_MultiInput()
      inp1 = torch.tensor([[23.0, 100.0, 0.0], [20.0, 50.0, 30.0]])
      inp2 = torch.tensor([[20.0, 50.0, 30.0], [0.0, 100.0, 0.0]])
      inp3 = torch.tensor([[0.0, 100.0, 10.0], [2.0, 10.0, 3.0]])
      expected = (
          [[444.0, 444.0, 444.0], [328.0, 328.0, 328.0]],
          [[68.0, 188.0, 108.0], [-12.0, 388.0, -12.0]],
          [[368.0, 368.0, 24.0], [0.0, 0.0, -12.0]],
      )
      self._occlusion_test_assert(
          net,
          (inp1, inp2, inp3),
          expected,
          baselines=(
              torch.tensor([[1.0, 4, 7], [3.0, 6, 9]]),
              3.0,
              torch.tensor([[4.0], [6]]),
          ),
          additional_input=(1,),
          sliding_window_shapes=((3,), (1,), (2,)),
          strides=(2, 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 13 for calling the Test obj's underlying member method code with example usage: obj.test_multi_input_ablation_with_baselines() without return types