(self, model, metric=None, pass_model=False, **kwargs)
If metric and pass_model are both defaults, this is effectively
        a sink.

        :param model: river model or pipeline
        :param metric: river metric
            If given, it is emitted on every sample
        :param pass_model: bool
            If True, the (updated) model if emitted for each sample
def __init__(self, model, metric=None, pass_model=False, **kwargs):
        """

        If metric and pass_model are both defaults, this is effectively
        a sink.

        :param model: river model or pipeline
        :param metric: river metric
            If given, it is emitted on every sample
        :param pass_model: bool
            If True, the (updated) model if emitted for each sample
        """
        super().__init__(**kwargs)
        self.model = model
        if pass_model and metric is not None:
            raise TypeError
        self.pass_model = pass_model
        self.metric = metric
def __init__ ( self , model , metric = None , pass_model = False , * * kwargs ) : super ( ) . __init__ ( * * kwargs ) self . model = model if pass_model and metric is not None : raise TypeError self . pass_model = pass_model self . metric = metric