def METHOD_NAME(self) -> None:
    model = BasicModel_MultiLayer()
    model.eval()
    inputs = torch.tensor([[10.0, 20.0, 10.0]])
    baselines = torch.randn(30, 3)
    gs = GradientShap(model)
    expected, delta = gs.attribute(
        inputs, baselines, target=0, return_convergence_delta=True
    )
    self.setUp()
    self._assert_attributions(
        model,
        model.linear0,
        inputs,
        baselines,
        0,
        expected,
        expected_delta=delta,
        attribute_to_layer_input=True,
    )