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

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

        - Univariate continuous distribution
        - Support: :math:`\\mathbb{R}_{>0}`.
        - Parameters: shape :math:`\\alpha > 0` and rate :math:`\\beta > 0`.

        Parameters
        ----------
        prior_alpha
            shape :math:`\\alpha` of the prior gamma distribution (default: None).
        prior_beta
            rate :math:`\\beta` of the prior gamma distribution (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.Gamma,
            parameter_names=["alpha", "beta"],
            prior_strength=prior_strength,
        )

        Gamma distribution.

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

        - Univariate continuous distribution
        - Support: :math:`\mathbb{R}_{>0}`.
        - Parameters: shape :math:`\alpha > 0` and rate :math:`\beta > 0`.

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