def __init__()

in torch_geometric_utils.py [0:0]

• 12 lines of code
• 5 McCabe index (conditional complexity)

    def __init__(self, aggr="add", flow="source_to_target"):
        super(MessagePassing, self).__init__()

        self.aggr = aggr
        assert self.aggr in ["add", "mean", "max"]

        self.flow = flow
        assert self.flow in ["source_to_target", "target_to_source"]

        self.__message_args__ = getargspec(self.message)[0][1:]
        self.__special_args__ = [
            (i, arg) for i, arg in enumerate(self.__message_args__) if arg in special_args
        ]
        self.__message_args__ = [arg for arg in self.__message_args__ if arg not in special_args]
        self.__update_args__ = getargspec(self.update)[0][2:]