def METHOD_NAME(self) -> None:
    num_in = 40
    input = torch.arange(0.0, num_in * 3.0, requires_grad=True).reshape(3, num_in)
    baselines = 0
    model = SoftmaxDeepLiftModel(num_in, 20, 10)
    dl = DeepLift(model)
    self.softmax_classification(
        model, dl, input, baselines, torch.tensor([2, 2, 2])
    )