def METHOD_NAME(self):
    # get model configs
    self.feature_names = self.cfg.MODEL.feature_names
    self.feature_dims = self.cfg.MODEL.feature_dims
    self.num_classes = self.cfg.MODEL.num_classes
    self.embedding_size = self.cfg.MODEL.embedding_size
    self.lstm_size = self.cfg.MODEL.lstm_size
    self.drop_rate = self.cfg.MODEL.drop_rate
    # get mode configs
    self.batch_size = self.get_config_from_sec(self.mode, 'batch_size', 1)
    self.num_gpus = self.get_config_from_sec(self.mode, 'num_gpus', 1)
    if self.mode == 'train':
        self.learning_rate = self.get_config_from_sec(
            'train', 'learning_rate', 1e-3)
        self.weight_decay = self.get_config_from_sec(
            'train', 'weight_decay', 8e-4)
        self.num_samples = self.get_config_from_sec('train', 'num_samples',
                                                    5000000)
        self.decay_epochs = self.get_config_from_sec(
            'train', 'decay_epochs', [5])
        self.decay_gamma = self.get_config_from_sec('train', 'decay_gamma',
                                                    0.1)