update
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@@ -5,13 +5,11 @@
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@Email: johnjim0816@gmail.com
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@Date: 2020-06-12 00:48:57
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@LastEditor: John
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LastEditTime: 2021-03-30 16:59:19
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LastEditTime: 2021-04-04 00:26:47
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@Discription:
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@Environment: python 3.7.7
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'''
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import sys,os
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from pathlib import Path
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import sys,os
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curr_path = os.path.dirname(__file__)
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parent_path=os.path.dirname(curr_path)
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sys.path.append(parent_path) # add current terminal path to sys.path
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@@ -21,19 +19,13 @@ import torch
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import datetime
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from DQN.agent import DQN
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from common.plot import plot_rewards
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from common.utils import save_results
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from common.utils import save_results,make_dir,del_empty_dir
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SEQUENCE = datetime.datetime.now().strftime("%Y%m%d-%H%M%S") # obtain current time
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SAVED_MODEL_PATH = curr_path+"/saved_model/"+SEQUENCE+'/' # path to save model
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if not os.path.exists(curr_path+"/saved_model/"):
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os.mkdir(curr_path+"/saved_model/")
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if not os.path.exists(SAVED_MODEL_PATH):
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os.mkdir(SAVED_MODEL_PATH)
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RESULT_PATH = curr_path+"/results/"+SEQUENCE+'/' # path to save rewards
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if not os.path.exists(curr_path+"/results/"):
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os.mkdir(curr_path+"/results/")
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if not os.path.exists(RESULT_PATH):
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os.mkdir(RESULT_PATH)
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make_dir(curr_path+"/saved_model/",curr_path+"/results/")
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del_empty_dir(curr_path+"/saved_model/",curr_path+"/results/")
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class DQNConfig:
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def __init__(self):
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@@ -72,8 +64,7 @@ def train(cfg,env,agent):
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rewards.append(ep_reward)
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# 计算滑动窗口的reward
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if ma_rewards:
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ma_rewards.append(
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0.9*ma_rewards[-1]+0.1*ep_reward)
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ma_rewards.append(0.9*ma_rewards[-1]+0.1*ep_reward)
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else:
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ma_rewards.append(ep_reward)
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print('Complete training!')
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@@ -87,6 +78,8 @@ if __name__ == "__main__":
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action_dim = env.action_space.n
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agent = DQN(state_dim,action_dim,cfg)
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rewards,ma_rewards = train(cfg,env,agent)
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make_dir(SAVED_MODEL_PATH,RESULT_PATH)
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agent.save(path=SAVED_MODEL_PATH)
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save_results(rewards,ma_rewards,tag='train',path=RESULT_PATH)
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plot_rewards(rewards,ma_rewards,tag="train",algo = cfg.algo,path=RESULT_PATH)
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del_empty_dir(SAVED_MODEL_PATH,RESULT_PATH)
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