KataGo/Linux:修订间差异
跳到导航
跳到搜索
此页面具有访问限制。如果您看见此消息,则说明您没有权限访问此页面。
无编辑摘要 |
(→編譯) |
||
(未显示同一用户的51个中间版本) | |||
第1行: | 第1行: | ||
'''KataGo'''是 | '''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<code>g4dn.xlarge</code>測試的 。 | |||
== 編譯 == | == 編譯 == | ||
先安裝需要的套件: | |||
<syntaxhighlight lang="bash"> | |||
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> | |||
再來編譯: | |||
<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; renice 20 $$; make -j | |||
</syntaxhighlight> | |||
然後把KataGo的執行檔丟到[[Lizzie]]目錄下: | |||
<syntaxhighlight lang="bash"> | |||
cd ~/KataGo/cpp; cp katago ~/Lizzie | |||
</syntaxhighlight> | |||
另外一種方式是編Eigen的版本: | |||
<syntaxhighlight lang="bash"> | |||
cd ~; git clone https://github.com/lightvector/KataGo.git; cd ~/KataGo/cpp; cmake . -DBUILD_MCTS=1 -DUSE_BACKEND=EIGEN -DUSE_AVX2=1 -DUSE_TCMALLOC=1; renice 20 $$; make -j | |||
</syntaxhighlight> | |||
== 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: | |||
<syntaxhighlight lang="bash"> | |||
cd ~/KataGo/cpp; cp configs/gtp_example.cfg ~/Lizzie/ | |||
</syntaxhighlight> | |||
== 下載最新的訓練資料 == | |||
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/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> | ||
== 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): | |||
<syntaxhighlight lang="bash"> | |||
nvidia-smi | |||
</syntaxhighlight> | |||
接下來可以跑KataGo的測試: | |||
<syntaxhighlight lang="bash"> | |||
cd ~/KataGo/; ./katago benchmark -model g170e-b20c256x2-s3761649408-d809581368/model.bin.gz -config gtp_example.cfg | |||
</syntaxhighlight> | |||
跑完測試後可以依照建議修改<code>gtp_example.cfg</code>裡的<code>numSearchThreads</code>以加快速度。 | |||
== 快速安裝 == | |||
這邊包括了KataGo、[[Lizzie]]以及[[VNC]]相關的套件。 | |||
<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 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 . -DBUILD_MCTS=1 -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 . -DBUILD_MCTS=1 -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> | |||
== 相關連結 == | |||
* [[KataGo]] | |||
* [[Lizzie]] | |||
== 參考資料 == | |||
{{Reflist|2}} | |||
== 外部連結 == | == 外部連結 == | ||
* {{Official|https://github.com/lightvector/KataGo}} {{en}} | * {{Official|https://github.com/lightvector/KataGo}} {{en}} | ||
[[Category:軟體]] |
2022年1月5日 (三) 13:24的最新版本
KataGo/Linux说明怎么在Linux系统上使用KataGo。
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 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
云端上面可能已经有显卡的驱动了,这时候不要装Nvidia驱动:
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; renice 20 $$; make -j
然后把KataGo的执行档丢到Lizzie目录下:
cd ~/KataGo/cpp; cp katago ~/Lizzie
另外一种方式是编Eigen的版本:
cd ~; git clone https://github.com/lightvector/KataGo.git; cd ~/KataGo/cpp; cmake . -DBUILD_MCTS=1 -DUSE_BACKEND=EIGEN -DUSE_AVX2=1 -DUSE_TCMALLOC=1; renice 20 $$; make -j
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
最新的训练资料可以在KataGo Distributed Training取得[1]。
这边会下载先前最强的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/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
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 g170e-b20c256x2-s3761649408-d809581368/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 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 . -DBUILD_MCTS=1 -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
云端上面不装显卡的驱动:
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 . -DBUILD_MCTS=1 -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
重开机后连进去再跑:
cd ~/Lizzie; ./katago benchmark -model g170e-b20c256x2-s3761649408-d809581368/model.bin.gz -config gtp_example.cfg
执行
先把VNC跑起来:
tightvncserver -geometry 1680x1050 -depth 24
透过VNC连进去后,用终端机(Terminal,预设是xterm)后执行Lizzie:
cd ~/Lizzie; java -jar lizzie.jar
另外也可以考虑设定sun.java2d.opengl
让画面比较不卡:
cd ~/Lizzie; java -Dsun.java2d.opengl=true -jar lizzie.jar
相关连结
参考资料
- ↑ KataGo Distributed Training. [2020-01-24] (English).
外部链接
- 官方网站 (英文)