def __init__(self, prior_alpha=None, prior_beta=None, prior_strength=1.0):
        """
        Beta distribution.

        https://en.wikipedia.org/wiki/Beta_distribution

        - Univariate continuous distribution.
        - Support: open interval :math:`(0,1)`
        - Parameters: shape parameters :math:`\\alpha > 0` and :math:`\\beta > 0`.

        Parameters
        ----------
        prior_alpha
            shape parameter :math:`\\alpha` of the Beta distribution, strictly positive (default: None)
        prior_beta
            shape parameter :math:`\\beta` distribution, strictly positive (default: None)
        prior_strength
            strength of the loss regularisation induced by the prior
        """
        self.prior_alpha = prior_alpha
        self.prior_beta = prior_beta
        _check_strict_positive(self.prior_alpha, "alpha")
        _check_strict_positive(self.prior_beta, "beta")

        self.softplus = nn.Softplus()
        super().__init__(
            likelihood_type=LikelihoodType.Beta,
            parameter_names=["alpha", "beta"],
            prior_strength=prior_strength,
        )

        Beta distribution.

        https://en.wikipedia.org/wiki/Beta_distribution

        - Univariate continuous distribution.
        - Support: open interval :math:`(0,1)`
        - Parameters: shape parameters :math:`\alpha > 0` and :math:`\beta > 0`.

        Parameters
        ----------
        prior_alpha
            shape parameter :math:`\alpha` of the Beta distribution, strictly positive (default: None)
        prior_beta
            shape parameter :math:`\beta` distribution, strictly positive (default: None)
        prior_strength
            strength of the loss regularisation induced by the prior
        
darts/utils/likelihood_models/torch.py