def __init__(self):
        """
        Negative Binomial distribution.

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

        It does not support priors.

        - Univariate discrete distribution.
        - Support: :math:`\\mathbb{N}_0` (natural numbers including 0).
        - Parameters: number of failures :math:`r > 0`, success probability :math:`p \\in (0, 1)`.

        Behind the scenes the distribution is reparameterized so that the actual outputs of the
        network are in terms of the mean :math:`\\mu` and shape :math:`\\alpha`.
        """
        self.softplus = nn.Softplus()
        super().__init__(
            likelihood_type=LikelihoodType.NegativeBinomial,
            parameter_names=["r", "p"],
            prior_strength=1.0,
        )

        Negative Binomial distribution.

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

        It does not support priors.

        - Univariate discrete distribution.
        - Support: :math:`\mathbb{N}_0` (natural numbers including 0).
        - Parameters: number of failures :math:`r > 0`, success probability :math:`p \in (0, 1)`.

        Behind the scenes the distribution is reparameterized so that the actual outputs of the
        network are in terms of the mean :math:`\mu` and shape :math:`\alpha`.
        
darts/utils/likelihood_models/torch.py