“KataGo”的版本间的差异

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sudo apt update; sudo apt install -y build-essential cmake default-jdk git libboost-filesystem-dev libgoogle-perftools-dev libzip-dev nvidia-435 ocl-icd-opencl-dev unzip zlib1g-dev; cd /tmp; wget https://github.com/featurecat/lizzie/releases/download/0.7.2/Lizzie.0.7.2.Mac-Linux.zip; cd ~; unzip /tmp/Lizzie.0.7.2.Mac-Linux.zip; git clone https://github.com/lightvector/KataGo.git; cd KataGo/cpp; cmake . -DBUILD_MCTS=1 -DUSE_BACKEND=OPENCL -DUSE_TCMALLOC=1; make -j8; cp configs/gtp_example.cfg ~/Lizzie; cd ~/Lizzie; wget https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b40c256x2-s1349368064-d524332537.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b30c320x2-s1287828224-d525929064.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170e-b20c256x2-s2430231552-d525879064.zip; echo *.zip | xargs -n1 unzip; sudo reboot
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sudo apt update; sudo apt install -y build-essential cmake default-jdk git libboost-filesystem-dev libgoogle-perftools-dev libzip-dev nvidia-compute-utils-435 nvidia-driver-435 nvidia-headless-435 nvidia-utils-435 ocl-icd-opencl-dev unzip zlib1g-dev; cd /tmp; wget https://github.com/featurecat/lizzie/releases/download/0.7.2/Lizzie.0.7.2.Mac-Linux.zip; cd ~; unzip /tmp/Lizzie.0.7.2.Mac-Linux.zip; git clone https://github.com/lightvector/KataGo.git; cd KataGo/cpp; cmake . -DBUILD_MCTS=1 -DUSE_BACKEND=OPENCL -DUSE_TCMALLOC=1; make -j8; cp configs/gtp_example.cfg ~/Lizzie; cd ~/Lizzie; wget https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b40c256x2-s1349368064-d524332537.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b30c320x2-s1287828224-d525929064.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170e-b20c256x2-s2430231552-d525879064.zip; echo *.zip | xargs -n1 unzip; sudo reboot
 
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2020年3月7日 (六) 20:58的版本

KataGo是一套电脑围棋软件。

基本环境

这边是用AWS上的Ubuntu 18.04,开g4dn.xlarge测试的。

编译

先安装需要的套件:

sudo apt install -y build-essential cmake git libboost-filesystem-dev libgoogle-perftools-dev libzip-dev nvidia-compute-utils-435 nvidia-driver-435 nvidia-headless-435 nvidia-utils-435 ocl-icd-opencl-dev unzip zlib1g-dev

再来编译:

cd ~; git clone https://github.com/lightvector/KataGo.git; cd ~/KataGo/cpp; cmake . -DBUILD_MCTS=1 -DUSE_BACKEND=OPENCL -DUSE_TCMALLOC=1; make -j8

设定

等下会使用Lizzie当作前端,所以这边会把KataGo的设定档丢到Lizzie的目录下:

cd KataGo/cpp; cp configs/gtp_example.cfg ~/Lizzie/

下载最新的训练资料

这边会下载目前最强的20 blocks、30 blocks与40 blocks版本到Lizzie的目录下并且解开:

cd ~/Lizzie/; wget https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b40c256x2-s1349368064-d524332537.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b30c320x2-s1287828224-d525929064.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170e-b20c256x2-s2430231552-d525879064.zip; echo *.zip | xargs -n1 unzip

测试

先测试Nvidia显卡有没有生效(要记得先重开机让驱动程式生效):

nvidia-smi

接下来可以跑KataGo的测试:

cd ~/KataGo/; ./katago benchmark -model g170-b40c256x2-s1349368064-d524332537/model.bin.gz -config gtp_example.cfg

跑完测试后可以依照建议修改gtp_example.cfg里的numSearchThreads以加快速度。

快速安装

sudo apt update; sudo apt install -y build-essential cmake default-jdk git libboost-filesystem-dev libgoogle-perftools-dev libzip-dev nvidia-compute-utils-435 nvidia-driver-435 nvidia-headless-435 nvidia-utils-435 ocl-icd-opencl-dev unzip zlib1g-dev; cd /tmp; wget https://github.com/featurecat/lizzie/releases/download/0.7.2/Lizzie.0.7.2.Mac-Linux.zip; cd ~; unzip /tmp/Lizzie.0.7.2.Mac-Linux.zip; git clone https://github.com/lightvector/KataGo.git; cd KataGo/cpp; cmake . -DBUILD_MCTS=1 -DUSE_BACKEND=OPENCL -DUSE_TCMALLOC=1; make -j8; cp configs/gtp_example.cfg ~/Lizzie; cd ~/Lizzie; wget https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b40c256x2-s1349368064-d524332537.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b30c320x2-s1287828224-d525929064.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170e-b20c256x2-s2430231552-d525879064.zip; echo *.zip | xargs -n1 unzip; sudo reboot

重开机后连进去再跑:

cd ~/KataGo; ./katago benchmark -model g170-b40c256x2-s1349368064-d524332537/model.bin.gz -config gtp_example.cfg

相关连结

外部链接