katago安装使用

看了今天柯洁和大申的比赛, AI还是太强了

本文介绍的是windows下如何配置

项目下载地址: https://github.com/lightvector/KataGo/releases

有显卡的推荐opencl版本, 作者推荐理由

OpenCL vs CUDA vs Eigen

KataGo has three backends, OpenCL (GPU), CUDA (GPU), and Eigen (CPU).

The quick summary is:

• Use OpenCL if you have any good or decent GPU.
• Use Eigen with AVX2 if you don’t have a GPU or if your GPU is too old/weak to work with OpenCL, and you just want a plain CPU KataGo.
• Use Eigen without AVX2 if your CPU is old or on a low-end device that doesn’t support AVX2.
• You can try CUDA you have a top-end NVIDIA FP16 + tensor-core GPU and you are willing to go through the hassle to install CUDA+CUDNN. It might or might not be faster than OpenCL, you can try it out to see.

一. katago下载解压

二. 神经网络选择

• g170-b30c320x2-s4824661760-d1229536699 (“g170 30 block d1229M”) - Final 30 block network!
• g170-b40c256x2-s5095420928-d1229425124 (“g170 40 block d1229M”) - Final 40 block network!
• g170e-b20c256x2-s5303129600-d1228401921 (“g170e 20 block d1228M”) - Final 20 block network!

Which Network Should I Use?

• For weaker or mid-range GPUs, try the final 20-block network.
• For top-tier GPUs and/or for the highest-quality analysis if you’re going to use many thousands and thousands of playouts and long thinking times, try the final 40-block network, which is more costly to run but should be the strongest and best.
• If you care a lot about theoretical purity - no outside data, bot learns strictly on its own - use the 20 or 40 block nets from this release, which are pure in this way and still much stronger than Leela Zero, but also not quite as strong as these final nets here.
• If you want some nets that are much faster to run, and each with their own interesting style of play due to their unique stages of learning, try any of the “b10c128” or “b15c192” Extended Training Nets here which are 10 block and 15 block networks from earlier in the run that are much weaker but still pro-level-and-beyond.
• And if you want to see how a super ultra large/slow network performs that nobody has tested until now, try the fat 40-block 384 channel network mentioned a little up above.

简而言之, b20,30,40是一个比一个强, 有显卡的选择b40, 在 v1.4.5 下载

将下载的神经网络文件放到katago同一目录

三. sabaki GUI安装

项目地址: https://github.com/SabakiHQ/Sabaki/releases

四. katago 配置

①在终端打开 katago文件夹, 输入

katago.exe genconfig -model g170-b30c320x2-s4824661760-d1229536699.bin.gz -output gtp_g170_b30.cfg

文件名无所谓

②之后会提示你选择规则, 选择chinese

③再就是读秒的时间, 默认就是n, 直接回车就好

④接下来是让你选择显卡, 根据自己的情况来选择, 譬如我有一张1050的卡, 我可以选择 1

⑤之后等待计算就行了

⑥最后有提示你如何在sabaki如何配置

五. sabaki配置

①修改语言为中文 , File —>Preferences

②选择引擎-显示引擎侧边栏

③点击左边播放符号—>管理引擎—>新增

④点击播放符号就能看到引擎

⑤右键引擎设为分析器可以看到棋局分析

⑥对局可以自己选择, 是否手动

然后就可以玩耍了