「KataGo/Linux」：修訂間差異

出自Gea-Suan Lin's Wiki
跳至導覽 跳至搜尋
← 較舊編輯
Gslin（留言 | 貢獻）
行政員、​介面管理員、​管理員
5,832筆編輯
Gslin（留言 | 貢獻）
行政員、​介面管理員、​管理員
5,832筆編輯
 
（未顯示同一使用者於中間所作的 36 次修訂）
第1行： 第1行：
'''KataGo'''是一套電腦圍棋軟體。
'''KataGo/Linux'''說明怎麼在[[Linux]]系統上使用[[KataGo]]。


== 基本環境 ==
== 基本環境 ==
第10行： 第10行：


<syntaxhighlight lang="bash">
<syntaxhighlight lang="bash">
sudo apt install -y build-essential cmake git libboost-filesystem-dev libgoogle-perftools-dev libzip-dev nvidia-435 ocl-icd-opencl-dev zlib1g-dev
sudo apt install -y build-essential cmake clinfo 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 wget zlib1g-dev
</syntaxhighlight>
 
雲端上面可能已經有顯示卡的驅動了，這時候不要裝Nvidia驅動：
 
<syntaxhighlight lang="bash">
sudo apt install -y build-essential clinfo cmake git libboost-filesystem-dev libgoogle-perftools-dev libzip-dev ocl-icd-opencl-dev unzip zlib1g-dev
</syntaxhighlight>
</syntaxhighlight>


第16行： 第22行：


<syntaxhighlight lang="bash">
<syntaxhighlight lang="bash">
cd ~; git clone https://github.com/lightvector/KataGo.git; cd ~/KataGo/cpp; cmake . -DBUILD_MCTS=1 -DUSE_BACKEND=OPENCL -DUSE_TCMALLOC=1; make -j8
cd ~; git clone https://github.com/lightvector/KataGo.git; cd ~/KataGo/cpp; cmake . -DUSE_BACKEND=OPENCL -DUSE_TCMALLOC=1; renice 20 $$; make -j16
</syntaxhighlight>
 
然後把KataGo的執行檔丟到[[Lizzie]]目錄下：
 
<syntaxhighlight lang="bash">
cd ~/KataGo/cpp; cp katago ~/Lizzie
</syntaxhighlight>
 
另外一種方式是編Eigen的版本：
 
<syntaxhighlight lang="bash">
cd ~; git clone https://github.com/lightvector/KataGo.git; cd ~/KataGo/cpp; cmake . -DUSE_BACKEND=EIGEN -DUSE_AVX2=1 -DUSE_TCMALLOC=1; renice 20 $$; make -j16
</syntaxhighlight>
</syntaxhighlight>


第24行： 第42行：


<syntaxhighlight lang="bash">
<syntaxhighlight lang="bash">
cd KataGo/cpp; cp configs/gtp_example.cfg ~/Lizzie/
cd ~/KataGo/cpp; cp configs/gtp_example.cfg ~/Lizzie/
</syntaxhighlight>
</syntaxhighlight>


== 下載最新的訓練資料 ==
== 下載最新的訓練資料 ==


這邊會下載目前最強的20 blocks、30 blocks與40 blocks版本到[[Lizzie]]的目錄下並且解開：
最新的訓練資料可以在KataGo Distributed Training取得<ref>{{Cite web |url=https://katagotraining.org/ |title=KataGo Distributed Training |language=en |accessdate=2020-01-24}}</ref>。
 
這邊會下載先前最強的20 blocks、30 blocks與40 blocks版本到[[Lizzie]]的目錄下並且解開：


<syntaxhighlight lang="bash">
<syntaxhighlight lang="bash">
cd ~/Lizzie/; wget https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b40c256x2-s1349368064-d524332537.zip; wget https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b30c320x2-s1287828224-d525929064.zip; wget https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170e-b20c256x2-s2430231552-d525879064.zip; echo *.zip | xargs -n1 unzip
cd ~/Lizzie/; wget https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170e-b20c256x2-s3761649408-d809581368.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b30c320x2-s2846858752-d829865719.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b40c256x2-s2990766336-d830712531.zip; echo *.zip | xargs -n1 unzip
</syntaxhighlight>
</syntaxhighlight>


第46行： 第66行：


<syntaxhighlight lang="bash">
<syntaxhighlight lang="bash">
cd ~/KataGo/; ./katago benchmark -model g170-b40c256x2-s1349368064-d524332537/model.bin.gz -config gtp_example.cfg
cd ~/KataGo/; ./katago benchmark -model g170e-b20c256x2-s3761649408-d809581368/model.bin.gz -config gtp_example.cfg
</syntaxhighlight>
</syntaxhighlight>


第52行： 第72行：


== 快速安裝 ==
== 快速安裝 ==
這邊包括了KataGo、[[Lizzie]]以及[[VNC]]相關的套件。


<syntaxhighlight lang="bash">
<syntaxhighlight lang="bash">
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 zlib1g-dev; cd ~; wget https://github.com/featurecat/lizzie/releases/download/0.7.2/Lizzie.0.7.2.Mac-Linux.zip; unzip Lizzie.0.7.2.Mac-Linux.zip; cd ~; git clone https://github.com/lightvector/KataGo.git; cd ~/KataGo/cpp; cmake . -DBUILD_MCTS=1 -DUSE_BACKEND=OPENCL -DUSE_TCMALLOC=1; make -j8; cd ~/KataGo/cpp; cp configs/gtp_example.cfg ~/Lizzie/; cd ~/Lizzie/; wget https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b40c256x2-s1349368064-d524332537.zip; wget https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b30c320x2-s1287828224-d525929064.zip; wget https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170e-b20c256x2-s2430231552-d525879064.zip; echo *.zip | xargs -n1 unzip; ./katago benchmark -model g170-b40c256x2-s1349368064-d524332537/model.bin.gz -config gtp_example.cfg
sudo apt update; sudo apt install -y build-essential clinfo cmake default-jdk git icewm 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 tightvncserver unzip wget 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 . -DUSE_BACKEND=OPENCL -DUSE_TCMALLOC=1; make -j8; cp katago ~/Lizzie; cp configs/gtp_example.cfg ~/Lizzie; cd ~/Lizzie; wget https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170e-b20c256x2-s3761649408-d809581368.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b30c320x2-s2846858752-d829865719.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b40c256x2-s2990766336-d830712531.zip; echo *.zip | xargs -n1 unzip; sudo reboot
</syntaxhighlight>
 
雲端上面不裝顯示卡的驅動：
 
<syntaxhighlight lang="bash">
sudo apt update; sudo apt install -y build-essential clinfo cmake default-jdk git icewm libboost-filesystem-dev libgoogle-perftools-dev libzip-dev ocl-icd-opencl-dev tightvncserver unzip wget 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 . -DUSE_BACKEND=OPENCL -DUSE_TCMALLOC=1; make -j8; cp katago ~/Lizzie; cp configs/gtp_example.cfg ~/Lizzie; cd ~/Lizzie; wget https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170e-b20c256x2-s3761649408-d809581368.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b30c320x2-s2846858752-d829865719.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b40c256x2-s2990766336-d830712531.zip; echo *.zip | xargs -n1 unzip; sudo reboot
</syntaxhighlight>
 
重開機後連進去再跑：
 
<syntaxhighlight lang="bash">
cd ~/Lizzie; ./katago benchmark -model g170e-b20c256x2-s3761649408-d809581368/model.bin.gz -config gtp_example.cfg
</syntaxhighlight>
 
== 執行 ==
 
先把[[VNC]]跑起來：
 
<syntaxhighlight lang="bash">
tightvncserver -geometry 1680x1050 -depth 24
</syntaxhighlight>
 
透過VNC連進去後，用終端機（Terminal，預設是xterm）後執行[[Lizzie]]：
 
<syntaxhighlight lang="bash">
cd ~/Lizzie; java -jar lizzie.jar
</syntaxhighlight>
 
另外也可以考慮設定<code>sun.java2d.opengl</code>讓畫面比較不卡：
 
<syntaxhighlight lang="bash">
cd ~/Lizzie; java -Dsun.java2d.opengl=true -jar lizzie.jar
</syntaxhighlight>
</syntaxhighlight>


== 相關連結 ==
== 相關連結 ==


* [[KataGo]]
* [[Lizzie]]
* [[Lizzie]]
== 參考資料 ==
{{Reflist|2}}


== 外部連結 ==
== 外部連結 ==

於 2024年6月18日 (二) 17:51 的最新修訂

KataGo/Linux說明怎麼在Linux系統上使用KataGo。

基本環境

這邊是用AWS上的Ubuntu 18.04，開g4dn.xlarge測試的。

編譯

先安裝需要的套件： 

sudo apt install -y build-essential cmake clinfo 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 wget zlib1g-dev

雲端上面可能已經有顯示卡的驅動了，這時候不要裝Nvidia驅動： 

sudo apt install -y build-essential clinfo cmake git libboost-filesystem-dev libgoogle-perftools-dev libzip-dev ocl-icd-opencl-dev unzip zlib1g-dev

再來編譯： 

cd ~; git clone https://github.com/lightvector/KataGo.git; cd ~/KataGo/cpp; cmake . -DUSE_BACKEND=OPENCL -DUSE_TCMALLOC=1; renice 20 $$; make -j16

然後把KataGo的執行檔丟到Lizzie目錄下： 

cd ~/KataGo/cpp; cp katago ~/Lizzie

另外一種方式是編Eigen的版本： 

cd ~; git clone https://github.com/lightvector/KataGo.git; cd ~/KataGo/cpp; cmake . -DUSE_BACKEND=EIGEN -DUSE_AVX2=1 -DUSE_TCMALLOC=1; renice 20 $$; make -j16

設定

等下會使用Lizzie當作前端，所以這邊會把KataGo的設定檔丟到Lizzie的目錄下： 

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

下載最新的訓練資料

最新的訓練資料可以在KataGo Distributed Training取得[1]。

這邊會下載先前最強的20 blocks、30 blocks與40 blocks版本到Lizzie的目錄下並且解開： 

cd ~/Lizzie/; wget https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170e-b20c256x2-s3761649408-d809581368.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b30c320x2-s2846858752-d829865719.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b40c256x2-s2990766336-d830712531.zip; echo *.zip | xargs -n1 unzip

測試

先測試Nvidia顯卡有沒有生效（要記得先重開機讓驅動程式生效）： 

nvidia-smi

接下來可以跑KataGo的測試： 

cd ~/KataGo/; ./katago benchmark -model g170e-b20c256x2-s3761649408-d809581368/model.bin.gz -config gtp_example.cfg

跑完測試後可以依照建議修改gtp_example.cfg裡的numSearchThreads以加快速度。

快速安裝

這邊包括了KataGo、Lizzie以及VNC相關的套件。 

sudo apt update; sudo apt install -y build-essential clinfo cmake default-jdk git icewm 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 tightvncserver unzip wget 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 . -DUSE_BACKEND=OPENCL -DUSE_TCMALLOC=1; make -j8; cp katago ~/Lizzie; cp configs/gtp_example.cfg ~/Lizzie; cd ~/Lizzie; wget https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170e-b20c256x2-s3761649408-d809581368.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b30c320x2-s2846858752-d829865719.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b40c256x2-s2990766336-d830712531.zip; echo *.zip | xargs -n1 unzip; sudo reboot

雲端上面不裝顯示卡的驅動： 

sudo apt update; sudo apt install -y build-essential clinfo cmake default-jdk git icewm libboost-filesystem-dev libgoogle-perftools-dev libzip-dev ocl-icd-opencl-dev tightvncserver unzip wget 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 . -DUSE_BACKEND=OPENCL -DUSE_TCMALLOC=1; make -j8; cp katago ~/Lizzie; cp configs/gtp_example.cfg ~/Lizzie; cd ~/Lizzie; wget https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170e-b20c256x2-s3761649408-d809581368.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b30c320x2-s2846858752-d829865719.zip https://d3dndmfyhecmj0.cloudfront.net/g170/neuralnets/g170-b40c256x2-s2990766336-d830712531.zip; echo *.zip | xargs -n1 unzip; sudo reboot

重開機後連進去再跑： 

cd ~/Lizzie; ./katago benchmark -model g170e-b20c256x2-s3761649408-d809581368/model.bin.gz -config gtp_example.cfg

執行

先把VNC跑起來： 

tightvncserver -geometry 1680x1050 -depth 24

透過VNC連進去後，用終端機（Terminal，預設是xterm）後執行Lizzie： 

cd ~/Lizzie; java -jar lizzie.jar

另外也可以考慮設定sun.java2d.opengl讓畫面比較不卡： 

cd ~/Lizzie; java -Dsun.java2d.opengl=true -jar lizzie.jar

相關連結

參考資料

  1. ↑ KataGo Distributed Training. [2020-01-24] （English）. 

外部連結

取自「https://wiki.gslin.org/index.php?title=KataGo/Linux&oldid=5559」