update

codes/DDPG/task0.py

@@ -34,7 +34,7 @@ class DDPGConfig:
         self.env_name = env_name # 环境名称
         self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu") # 检测GPU
         self.train_eps = 300 # 训练的回合数
-        self.eval_eps = 50 # 测试的回合数
+        self.test_eps = 50 # 测试的回合数
         self.gamma = 0.99 # 折扣因子
         self.critic_lr = 1e-3 # 评论家网络的学习率
         self.actor_lr = 1e-4 # 演员网络的学习率

codes/DDPG/train.py

@@ -42,7 +42,7 @@ def test(cfg, env, agent):
     print(f'环境：{cfg.env_name}, 算法：{cfg.algo}, 设备：{cfg.device}')
     rewards = [] # 记录所有回合的奖励
     ma_rewards = []  # 记录所有回合的滑动平均奖励
-    for i_ep in range(cfg.eval_eps):
+    for i_ep in range(cfg.test_eps):
         state = env.reset() 
         done = False
         ep_reward = 0
@@ -59,6 +59,6 @@ def test(cfg, env, agent):
             ma_rewards.append(0.9*ma_rewards[-1]+0.1*ep_reward)
         else:
             ma_rewards.append(ep_reward)
-        print(f"回合：{i_ep+1}/{cfg.eval_eps}，奖励：{ep_reward:.1f}")
+        print(f"回合：{i_ep+1}/{cfg.test_eps}，奖励：{ep_reward:.1f}")
     print('完成测试！')
     return rewards, ma_rewards