def METHOD_NAME(self) -> None:
    num_in = 40
    input = torch.arange(0.0, num_in * 1.0, requires_grad=True).unsqueeze(0)
    baselines = torch.randn(5, 40)
    model = SoftmaxDeepLiftModel(num_in, 20, 10)
    dl = DeepLiftShap(model)
    self.softmax_classification(model, dl, input, baselines, torch.tensor(2))