update

codes/DQN/dqn.py

@@ -5,7 +5,7 @@
 @Email: johnjim0816@gmail.com
 @Date: 2020-06-12 00:50:49
 @LastEditor: John
-LastEditTime: 2022-07-13 00:08:18
+LastEditTime: 2022-07-20 23:57:16
 @Discription: 
 @Environment: python 3.7.7
 '''
@@ -64,8 +64,8 @@ class ReplayBuffer:
 class DQN:
     def __init__(self, n_states,n_actions,cfg):
 
-        self.n_actions = n_actions  # 总的动作个数
-        self.device = cfg.device  # 设备，cpu或gpu等
+        self.n_actions = n_actions  
+        self.device = torch.device(cfg.device)  # cpu or cuda
         self.gamma = cfg.gamma  # 奖励的折扣因子
         # e-greedy策略相关参数
         self.frame_idx = 0  # 用于epsilon的衰减计数

codes/DQN/outputs/CartPole-v0/20220713-211653/results/params.json

@@ -0,0 +1,19 @@
+{
+    "algo_name": "DQN",
+    "env_name": "CartPole-v0",
+    "train_eps": 200,
+    "test_eps": 20,
+    "gamma": 0.95,
+    "epsilon_start": 0.95,
+    "epsilon_end": 0.01,
+    "epsilon_decay": 500,
+    "lr": 0.0001,
+    "memory_capacity": 100000,
+    "batch_size": 64,
+    "target_update": 4,
+    "hidden_dim": 256,
+    "deivce": "cpu",
+    "result_path": "C:\\Users\\24438\\Desktop\\rl-tutorials/outputs/CartPole-v0/20220713-211653/results/",
+    "model_path": "C:\\Users\\24438\\Desktop\\rl-tutorials/outputs/CartPole-v0/20220713-211653/models/",
+    "save_fig": true
+}

codes/DQN/outputs/CartPole-v0/20220713-211653/results/params.txt

@@ -1,19 +0,0 @@
------------------- start ------------------
-algo_name : DQN
-env_name : CartPole-v0
-train_eps : 200
-test_eps : 20
-gamma : 0.95
-epsilon_start : 0.95
-epsilon_end : 0.01
-epsilon_decay : 500
-lr : 0.0001
-memory_capacity : 100000
-batch_size : 64
-target_update : 4
-hidden_dim : 256
-result_path : C:\Users\24438\Desktop\rl-tutorials\codes\DQN/outputs/CartPole-v0/20220713-211653/results/
-model_path : C:\Users\24438\Desktop\rl-tutorials\codes\DQN/outputs/CartPole-v0/20220713-211653/models/
-save_fig : True
-device : cuda
-------------------- end -------------------

codes/DQN/task0.py

@@ -1,12 +1,9 @@
-from lib2to3.pytree import type_repr
-import sys
-import os
-from parso import parse
+import sys,os
+curr_path = os.path.dirname(os.path.abspath(__file__))  # current path
+parent_path = os.path.dirname(curr_path)  # parent path
+sys.path.append(parent_path)  # add to system path
 import torch.nn as nn
 import torch.nn.functional as F
-curr_path = os.path.dirname(os.path.abspath(__file__))  # 当前文件所在绝对路径
-parent_path = os.path.dirname(curr_path)  # 父路径
-sys.path.append(parent_path)  # 添加路径到系统路径
 
 import gym
 import torch
@@ -35,14 +32,13 @@ def get_args():
     parser.add_argument('--batch_size',default=64,type=int)
     parser.add_argument('--target_update',default=4,type=int)
     parser.add_argument('--hidden_dim',default=256,type=int)
+    parser.add_argument('--device',default='cpu',type=str,help="cpu or cuda") 
     parser.add_argument('--result_path',default=curr_path + "/outputs/" + parser.parse_args().env_name + \
             '/' + curr_time + '/results/' )
     parser.add_argument('--model_path',default=curr_path + "/outputs/" + parser.parse_args().env_name + \
             '/' + curr_time + '/models/' ) # path to save models
     parser.add_argument('--save_fig',default=True,type=bool,help="if save figure or not")           
-    args = parser.parse_args()    
-    args.device = torch.device(
-            "cuda" if torch.cuda.is_available() else "cpu")  # check GPU                        
+    args = parser.parse_args()                          
     return args
 
 def env_agent_config(cfg,seed=1):