def METHOD_NAME(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]])
    baseline = torch.tensor([[1.0, 2.0, 3.0]])
    layer_mask = torch.tensor([[0, 1, 0], [0, 1, 2]])
    self._ablation_test_assert(
        net,
        net.model.linear1,
        (inp1, inp2, inp3),
        [[316.0, 992.0, 316.0], [84.0, 632.0, 120.0]],
        additional_input=(1,),
        baselines=baseline,
        perturbations_per_eval=(1, 2, 3),
        layer_mask=layer_mask,
        attribute_to_layer_input=True,
    )
    self._ablation_test_assert(
        net,
        net.model.linear0,
        (inp1, inp2, inp3),
        [[316.0, 992.0, 316.0], [84.0, 632.0, 120.0]],
        additional_input=(1,),
        baselines=baseline,
        layer_mask=layer_mask,
        perturbations_per_eval=(1, 2, 3),
    )