Sayuri
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AlphaZero based engine for the game of Go (圍棋/围棋).
Hi, I run cgf2023 weight on CGOS. But It seems Sayuri passes without removing all dead stones. http://www.yss-aya.com/cgos/viewer.cgi?19x19/SGF/2023/08/24/876080.sgf Is there any option to remove all dead stones? I use RTX...
问题棋局
Sayuri 执黑对 Zen7,很精彩的一局棋。309手收官后 黑胜0.5目,白棋pass 黑棋自填2手后pass,导致输1.5目,不知为何会这样? [sgf.zip](https://github.com/CGLemon/Sayuri/files/12737579/sgf.zip) 
clang-16: error: no such file or directory: 'accuracy/*.cc' delete.. accuracy/*.cc After deleting it, an error appears as follows. $ g++ -std=c++14 -ffast-math -I . -lpthread *.cc utils/*.cc game/*.cc mcts/*.cc neural/*.cc...
time_settings 200 20 1  
I'm using it well. Is it possible to do a cuda compile? for window use. Thank you.
g++ -std=c++14 -ffast-math -I . -Wall -Wextra -lpthread *.cc utils/*.cc accuracy/*.cc game/*.cc mcts/*.cc neural/*.cc neural/blas/*.cc neural/cuda/*.cc pattern/*.cc selfplay/*.cc -o Sayuri -O3 -DNDEBUG -DWIN32 -I ../third_party/Eigen -DUSE_BLAS -DUSE_EIGEN C:\Users\mong\AppData\Local\Temp\ccCYLsP0.o:convolution.cc:(.text+0x0): multiple definition...
g++ -std=c++14 -ffast-math -I . -Wall -Wextra -lpthread *.cc utils/*.cc accuracy/*.cc game/*.cc mcts/*.cc neural/*.cc neural/blas/*.cc neural/cuda/*.cc pattern/*.cc selfplay/*.cc -o Sayuri -O3 -DNDEBUG -DWIN32 -I ../third_party/Eigen -DUSE_BLAS -DUSE_EIGEN neural/blas/winograd_convolution3.cc: In lambda...
Hi, I would like to try out sayuri but only have igpu hd520 graphics. Is openCl possible in the future? Thanks.
作者您好,我一直在关注sayuri的训练过程(因为对gumbel是否能真正提升训练很感兴趣),我注意到您在最新的日志中和leelazero的早期网络进行了对比,但是据我所知leelazero在早期很长一段时间的训练有比较严重的问题(具体是什么忘了,很久以前的事了),所以如果想要对比训练速度的话和sai比leelazero更合适,考虑到sayuri使用了一些kata的算法来改进训练,如果想要证明gumbel有效可能和kata的早期网络对比是最合适的。
/home/guest/Sayuri/src/neural/cuda/cuda_layers.cc: In member function ‘void CUDA::Convolution::Forward(int, float*, float*, void*, void*, size_t)’: /home/guest/Sayuri/src/neural/cuda/cuda_layers.cc:126:15: warning: unused variable ‘board_size’ [-Wunused-variable] 126 | const int board_size = (width_ + height_) / 2; | ^~~~~~~~~~...