How to use the chaospy.distributions.operators.addition.Add.__init__ function in chaospy

def __init__(self, loc=0, scale=1, skew=1):
        self._repr = {"loc": loc, "scale": scale, "skew": skew}
        Add.__init__(self, left=logistic(skew)*scale, right=loc)

def __init__(self, shape=1, scale=1, shift=0):
        self._repr = {"shape": shape, "scale": scale, "shift": shift}
        Add.__init__(self, nakagami(shape)*scale, shift)

def __init__(self, loc=0, scale=1):
        self._repr = {"loc": loc, "scale": scale}
        Add.__init__(self, left=cauchy()*scale, right=loc)

def __init__(self, shape=0, scale=1, shift=0):
        self._repr = {"shape": shape, "scale": scale, "shift": shift}
        Add.__init__(self, left=tukey_lambda(shape)*scale, right=shift)

def __init__(self, scale=1, loc=0):
        self._repr = {"scale": scale, "loc": loc}
        Add.__init__(self, left=log_weibull()*scale, right=loc)

def __init__(self, mu=1, scale=1, shift=0):
        self._repr = {"mu": mu, "scale": scale, "shift": shift}
        Add.__init__(self, left=wald(mu)*scale, right=shift)

def __init__(self, alpha=1, kappa=1, scale=1, shift=0):
        self._repr = {
            "alpha": alpha, "kappa": kappa, "scale": scale, "shift": shift}
        Add.__init__(
            self, left=exponential_weibull(alpha, kappa)*scale, right=shift)

def __init__(self, shape=1, scale=1, shift=0):
        self._repr = {"shape": shape, "scale": scale, "shift": shift}
        Add.__init__(self, left=frechet(shape)*scale, right=shift)

def __init__(self, scale=1, shift=0):
        self._repr = {"scale": scale, "shift": shift}
        Add.__init__(self, left=chi(3)*scale, right=shift)