def METHOD_NAME(
    self, type: str = "vanilla", approximation_method: str = "gausslegendre"
) -> None:
    num_in = 40
    input = torch.arange(0.0, num_in * 3.0, requires_grad=True).reshape(3, num_in)
    target = torch.tensor([5, 5, 2])
    baseline = torch.zeros(1, num_in)
    # 10-class classification model
    model = SoftmaxModel(num_in, 20, 10)
    self._validate_completness(
        model, input, target, type, approximation_method, baseline
    )