Leela 的作者 Gian-Carlo Pascutto 依照 paper 的描述寫完了,放在 GitHub 上的 gcp/leela-zero:
I made an open source re-implementation of AlphaGo Zero: https://t.co/p8H6gGohA1
It just needs a good weights file.
— Gian-Carlo Pascutto (@gcpascutto) October 24, 2017
不過他在 Twitter 上也提到了,open source 實做不是真正的困難,真正的困難在於訓練完的資料,那個部份需要大量的成本才有辦法作到:
Every redditor is asking to opensource AlphaGo Zero, when all we really need are those last 500k self-play games.
— Gian-Carlo Pascutto (@gcpascutto) October 19, 2017
另外他推估 AlphaGo Zero 的計算量是 1700 年 (以 1080 Ti 來計算):「[Computer-go] Zero performance」。
另外 Leela 0.11.0 也推出了,還是先維持 policy + value 的方式,但引入了不少新演算法加強。另外一個蠻特別的地方是 Windows 版改用 clang 而變快不少:
Windows version is now compiled with Clang/LLVM 5.0 instead of MSVC2017. This makes the Monte Carlo evaluations about 15% faster.
雖然 DeepMind 說要收手,但還是留下不少方向讓大家走...