(self)
init
init
init
def __init__(self):
        """
            init
        """
        self.parse_args = self._init_parser()
        self.bl_decay = self.parse_args.bl_decay
        self.log_dir = self.parse_args.log_dir
        self.early_stop = self.parse_args.early_stop
        self.data_path = self.parse_args.data_path
        self.num_models = self.parse_args.num_models
        self.batch_size = self.parse_args.batch_size
        self.chunk_size= self.parse_args.chunk_size

        self._init_dir_path()
        self.model = PolicyModel(self.parse_args)
        algo_hyperparas = {'lr': self.parse_args.learning_rate}
        self.algorithm = ReinforcePolicyGradient(self.model,
                                                 hyperparas=algo_hyperparas)
        self.autodl_agent = AutoDLAgent(self.algorithm, self.parse_args)
        self.total_reward = 0
def __init__ ( self ) : self . parse_args = self . _init_parser ( ) self . bl_decay = self . parse_args . bl_decay self . log_dir = self . parse_args . log_dir self . early_stop = self . parse_args . early_stop self . data_path = self . parse_args . data_path self . num_models = self . parse_args . num_models self . batch_size = self . parse_args . batch_size self . chunk_size = self . parse_args . chunk_size self . _init_dir_path ( ) self . model = PolicyModel ( self . parse_args ) algo_hyperparas = { 'lr' : self . parse_args . learning_rate } self . algorithm = ReinforcePolicyGradient ( self . model , hyperparas = algo_hyperparas ) self . autodl_agent = AutoDLAgent ( self . algorithm , self . parse_args ) self . total_reward = 0