Method init_ema_model

ram/models/ram_base_model.py:46–56

(self)

            self.load_network(self.net_g, load_path, self.opt['path'].get('strict_load_g', True), param_key)

    def init_ema_model(self):
        logger = get_root_logger()
        logger.info(f'Use Exponential Moving Average with decay: {self.ema_decay}')
        self.net_g_ema = build_network(self.opt['network_g']).to(self.device)
        # 加载预训练模型或初始化权重
        load_path = self.opt['path'].get('pretrain_network_g', None)
        if load_path is not None:
            self.load_network(self.net_g_ema, load_path, self.opt['path'].get('strict_load_g', True), 'params_ema')
        else:
            self.model_ema(0)  # 初始化 EMA model 权重
        self.net_g_ema.eval()

    def model_ema(self, decay=0.999):
        net_g = self.get_bare_model(self.net_g)