用PARL训练mini-alphaGO

用PARL训练mini-alphaGO

今天尝试用PARL里面的代码跑一下mini-alphago的项目，是torch版本的。

下载代码和数据集

首先下载源代码，下载地址为：

​​ 1.4.0parl 1.4.1tqdm 4.60.0

建议用anaconda创建一个新的环境，把这三个包安装一下就行了。

训练

xparl start --port 8010 --cpu_num 5

上面的命令执行完以后，输出的日志为：

[04-14 11:53:35 MainThread @logger.py:242] Argv: /Users/wugaosheng/anaconda3/envs/alphago/bin/xparl start --port 8010 --cpu_num 5 # The Parl cluster is started at localhost:8010. # A local worker with 5 CPUs is connected to the cluster. # Starting the cluster monitor... ## If you want to check cluster status, please view: or call: xparl status ## If you want to add more CPU resources, please call: xparl connect --address 172.24.148.88:8010 ## If you want to shutdown the cluster, please call: xparl stopChecking status of log_server...# Start the log server sucessfully.

然后再执行

python main.py

就可以跑了，输出的日志为：

arning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.Deprecated in NumPy 1.20; for more details and guidance: self.np_pieces = np.zeros([self.height, self.width], dtype=np.int)[04-14 11:53:46 MainThread @client.py:431] Remote actors log url: 11:53:46 MainThread @Coach.py:73] Starting Iter #1 ...[04-14 11:53:46 MainThread @Coach.py:76] Step1: self-play in parallel...

然后你会发现你的电脑的风扇转速很快，声音变大了，说明正在运行哈。如果想等到训练结束，建议找个好一点的GPU机器哈。

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