Merge pull request LeelaChessZero#7 from LeelaChessZero/master

merge lc0 master

Author: Naphthalin

README.md

@@ -34,9 +34,11 @@ Having successfully acquired Lc0 via either of these methods, proceed to the bui
 
 Building should be easier now than it was in the past. Please report any problems you have.
 
-Aside from the git submodule, lc0 requires the Meson build system and at least one backend library for evaluating the neural network, as well as the required libraries `protobuf` and `zlib`. (`gtest` is optionally used for the test suite.) If your system already has those two libraries installed, they will be used; otherwise Meson will generate its own copy of the two (a "subproject"), which in turn requires that git is installed (yes, separately from cloning the actual lc0 repository). Meson also requires python and Ninja.
+Aside from the git submodule, lc0 requires the Meson build system and at least one backend library for evaluating the neural network, as well as the required `zlib`. (`gtest` is optionally used for the test suite.) If your system already has this library installed, they will be used; otherwise Meson will generate its own copy of the two (a "subproject"), which in turn requires that git is installed (yes, separately from cloning the actual lc0 repository). Meson also requires python and Ninja.
 
-Backend support includes (in theory) any CBLAS-compatible library for CPU usage, such as OpenBLAS or Intel's MKL. For GPUs, OpenCL and CUDA+cudnn are supported.
+Backend support includes (in theory) any CBLAS-compatible library for CPU usage, such as OpenBLAS or Intel's DNNL or MKL. For GPUs, OpenCL and CUDA+cudnn are supported, while DX-12 can be used in Windows 10 with latest drivers.
+
+Finally, lc0 requires a compiler supporting C++17. Minimal versions seem to be g++ v8.0, clang v5.0 (with C++17 stdlib) or Visual Studio 2017.
 
 Given those basics, the OS and backend specific instructions are below.
 
@@ -80,26 +82,31 @@ in ("Deep Learning").
 
 #### Ubuntu 18.04
 
-For Ubuntu 18.04 you need the latest version of meson and clang-6.0 before performing the steps above:
+For Ubuntu 18.04 you need the latest version of meson, g++-8 and clang-6.0 before performing the steps above:
 
-    sudo apt-get install clang-6.0 ninja-build pkg-config protobuf-compiler libprotobuf-dev meson
+    sudo apt-get install gcc-8 g++-8 clang-6.0 ninja-build pkg-config
+    pip3 install meson --user
     CC=clang-6.0 CXX=clang++-6.0 INSTALL_PREFIX=~/.local ./build.sh
 
 Make sure that `~/.local/bin` is in your `PATH` environment variable. You can now type `lc0 --help` and start.
 
 #### Ubuntu 16.04
 
-For Ubuntu 16.04 you need the latest version of meson and clang-6.0 before performing the steps above:
+For Ubuntu 16.04 you need the latest version of meson, ninja and also gcc-8.0 before performing the steps above:
 
-    wget -O - https://apt.llvm.org/llvm-snapshot.gpg.key | sudo apt-key add -
-    sudo apt-add-repository 'deb http://apt.llvm.org/xenial/ llvm-toolchain-xenial-6.0 main'
+    sudo add-apt-repository ppa:ubuntu-toolchain-r/test
     sudo apt-get update
-    sudo apt-get install clang-6.0 ninja-build protobuf-compiler libprotobuf-dev
+    sudo apt-get install gcc-8 g++-8
     pip3 install meson --user
-    CC=clang-6.0 CXX=clang++-6.0 INSTALL_PREFIX=~/.local ./build.sh
+    pip3 install ninja --user
+    CC=gcc-8 CXX=g++-8 INSTALL_PREFIX=~/.local ./build.sh
 
 Make sure that `~/.local/bin` is in your `PATH` environment variable. You can now type `lc0 --help` and start.
 
+If you want to build with clang-6.0 you still need g++-8 for the library. Replace the last line above with:
+
+    sudo apt-get install clang-6.0
+    CC=clang-6.0 CXX=clang++-6.0 INSTALL_PREFIX=~/.local ./build.sh
 
 #### openSUSE (all versions)
 
@@ -113,24 +120,23 @@ to run latest releases of lc0 and the client inside a Docker container.
 
 ### Windows
 
-0. Install Microsoft Visual Studio
-1. Install [CUDA](https://developer.nvidia.com/cuda-zone) (v9.2 is fine)
+Here are the brief instructions for CUDA/CuDNN, for details and other options see `windows-build.md`.
+
+0. Install Microsoft Visual Studio (2017 or later)
+1. Install [CUDA](https://developer.nvidia.com/cuda-zone)
 2. Install [cuDNN](https://developer.nvidia.com/cudnn).
 3. Install Python3
 4. Install Meson: `pip3 install --upgrade meson`
-5. Edit `build-cuda.cmd`:
+5. Edit `build.cmd`:
 
-* If you use MSVS other than 2015 (or if it's installed into non-standard location):
-    * `C:\Program Files (x86)\Microsoft Visual Studio 14.0\` replace 14.0 with your version
-    * `--backend 2015` replace 2015 with your version
-* `C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.2\lib\x64` replace with your CUDA path
-* `C:\dev\cuDNN\` replace with your cuDNN directory
+* Set `CUDA_PATH` with your CUDA directory
+* Set `CUDNN_PATH` with your cuDNN directory (may be the same with CUDA_PATH)
 
-6. Run `build-cuda.cmd`. It will generate MSVS project and pause.
+6. Run `build.cmd`. It will ask permission to delete the build directory, then generate MSVS project and pause.
 
 Then either:
 
-7. Hit <Enter> to build it.
+7. Hit `Enter` to build it.
 8. Resulting binary will be `build/lc0.exe`
 
 Or.

appveyor.yml

@@ -44,13 +44,12 @@ install:
 - cmd: set PATH=C:\Python36;C:\Python36\scripts;%PATH%
 - cmd: pip3 install --upgrade meson
 - cmd: call "C:\Program Files (x86)\Microsoft Visual Studio\2017\Community\VC\Auxiliary\Build\vcvarsall.bat" amd64
-- cmd: IF %NAME%==android C:\ProgramData\Microsoft\AndroidNDK64\android-ndk-r17\build\tools\make_standalone_toolchain.py --arch arm64 --api 21 --stl libc++ --install-dir \android-standalone-64
-- cmd: IF %NAME%==android set PATH=C:\android-standalone-64\bin;%PATH%
+- cmd: IF %NAME%==android IF NOT EXIST C:\ndk\android-ndk-r19c\toolchains\llvm\prebuilt\windows-x86_64 appveyor DownloadFile https://dl.google.com/android/repository/android-ndk-r19c-windows-x86_64.zip
+- cmd: IF %NAME%==android IF NOT EXIST C:\ndk\android-ndk-r19c\toolchains\llvm\prebuilt\windows-x86_64 7z x android-ndk-r19c-windows-x86_64.zip -oC:\ndk
+- cmd: IF %NAME%==android set PATH=C:\ndk\android-ndk-r19c\toolchains\llvm\prebuilt\windows-x86_64\bin;%PATH%
 - cmd: IF %NAME%==android sed "s/clang+*/&.cmd/" cross-files/aarch64-linux-android >crossfile-aarch64
 - cmd: IF %NAME%==android IF NOT EXIST C:\cache\OpenBLAS\android-aarch64 appveyor DownloadFile https://github.com/borg323/OpenBLAS/releases/download/android-0.3.8-2/openblas-android-aarch64.zip
 - cmd: IF %NAME%==android IF NOT EXIST C:\cache\OpenBLAS\android-aarch64 7z x openblas-android-aarch64.zip -oC:\cache\OpenBLAS
-- cmd: IF %NAME%==android C:\ProgramData\Microsoft\AndroidNDK64\android-ndk-r17\build\tools\make_standalone_toolchain.py --arch arm --api 21 --stl libc++ --install-dir \android-standalone-32
-- cmd: IF %NAME%==android set PATH=C:\android-standalone-32\bin;%PATH%
 - cmd: IF %NAME%==android sed "s/clang+*/&.cmd/" cross-files/armv7a-linux-android >crossfile-armv7a
 - cmd: IF %NAME%==android IF NOT EXIST C:\cache\OpenBLAS\android-armv7a appveyor DownloadFile https://github.com/borg323/OpenBLAS/releases/download/android-0.3.8-2/openblas-android-armv7a.zip
 - cmd: IF %NAME%==android IF NOT EXIST C:\cache\OpenBLAS\android-armv7a 7z x openblas-android-armv7a.zip -oC:\cache\OpenBLAS
@@ -68,14 +67,15 @@ cache:
   - C:\cache -> appveyor.yml
   - 'C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.0'
   - C:\projects\lc0\subprojects\packagecache
+  - C:\ndk\android-ndk-r19c\toolchains\llvm\prebuilt\windows-x86_64
 before_build:
 - cmd: git submodule update --init --recursive
 - cmd: SET BUILD_BLAS=%BLAS%
 - cmd: IF %OPENCL%==true SET BUILD_BLAS=true
 - cmd: IF %DX%==true SET BUILD_BLAS=true
 - cmd: SET EMBED=false
 - cmd: IF %APPVEYOR_REPO_TAG%==true IF %ANDROID%==true SET EMBED=true
-- cmd: IF %ANDROID%==false meson build --backend vs2017 --buildtype release -Dgtest=%GTEST% -Dopencl=%OPENCL% -Dblas=%BUILD_BLAS% -Ddnnl=true -Deigen=true -Ddx=%DX% -Dcudnn=%CUDA% -Dispc_native_only=false -Dpopcnt=false -Dcudnn_include="%CUDA_PATH%\include","%PKG_FOLDER%\cuda\include" -Dcudnn_libdirs="%CUDA_PATH%\lib\x64","%PKG_FOLDER%\cuda\lib\x64" -Dopenblas_include="%PKG_FOLDER%\OpenBLAS\dist64\include" -Dopenblas_libdirs="%PKG_FOLDER%\OpenBLAS\dist64\lib" -Ddnnl_dir="%PKG_FOLDER%\dnnl_win_1.1.1_cpu_vcomp" -Dopencl_include="%PKG_FOLDER%\opencl-nug.0.777.77\build\native\include" -Dopencl_libdirs="%PKG_FOLDER%\opencl-nug.0.777.77\build\native\lib\x64" -Ddefault_library=static
+- cmd: IF %ANDROID%==false meson build --backend vs2017 --buildtype release -Dgtest=%GTEST% -Dopencl=%OPENCL% -Dblas=%BUILD_BLAS% -Ddnnl=true -Ddx=%DX% -Dcudnn=%CUDA% -Dispc_native_only=false -Dpopcnt=false -Dcudnn_include="%CUDA_PATH%\include","%PKG_FOLDER%\cuda\include" -Dcudnn_libdirs="%CUDA_PATH%\lib\x64","%PKG_FOLDER%\cuda\lib\x64" -Dopenblas_include="%PKG_FOLDER%\OpenBLAS\dist64\include" -Dopenblas_libdirs="%PKG_FOLDER%\OpenBLAS\dist64\lib" -Ddnnl_dir="%PKG_FOLDER%\dnnl_win_1.1.1_cpu_vcomp" -Dopencl_include="%PKG_FOLDER%\opencl-nug.0.777.77\build\native\include" -Dopencl_libdirs="%PKG_FOLDER%\opencl-nug.0.777.77\build\native\lib\x64" -Ddefault_library=static
 - cmd: IF %ANDROID%==true meson arm64-v8a --buildtype release -Dgtest=false -Dopenblas_include="%PKG_FOLDER%\OpenBLAS\android-aarch64\include" -Dopenblas_libdirs="%PKG_FOLDER%\OpenBLAS\android-aarch64\lib" -Dembed=%EMBED% -Ddefault_library=static --cross-file crossfile-aarch64
 - cmd: IF %ANDROID%==true meson armeabi-v7a --buildtype release -Dgtest=false -Dopenblas_include="%PKG_FOLDER%\OpenBLAS\android-armv7a\include" -Dopenblas_libdirs="%PKG_FOLDER%\OpenBLAS\android-armv7a\lib" -Dembed=%EMBED% -Ddefault_library=static --cross-file crossfile-armv7a
 build_script:

build-cl.cmd

@@ -0,0 +1,62 @@
+@echo off
+setlocal
+
+rem 1. Set the following for the options you want to build.
+set CUDNN=true
+set DX12=false
+set OPENCL=false
+set MKL=false
+set DNNL=false
+set OPENBLAS=false
+set EIGEN=false
+set TEST=false
+
+rem 2. Edit the paths for the build dependencies.
+set CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.0
+set CUDNN_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.0
+set OPENBLAS_PATH=C:\OpenBLAS
+set MKL_PATH=C:\Program Files (x86)\IntelSWTools\compilers_and_libraries\windows\mkl
+set DNNL_PATH=C:\dnnl_win_1.1.1_cpu_vcomp
+set OPENCL_LIB_PATH=%CUDA_PATH%\lib\x64
+set OPENCL_INCLUDE_PATH=%CUDA_PATH%\include
+
+rem 3. In most cases you won't need to change anything further down.
+echo Deleting build directory:
+rd /s build
+
+if exist "C:\Program Files (x86)\Microsoft Visual Studio\2019" (
+  call "C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Auxiliary\Build\vcvarsall.bat" amd64
+  set MSBuild=msbuild
+  set backend=vs2019
+) else (
+  call "C:\Program Files (x86)\Microsoft Visual Studio\2017\Community\VC\Auxiliary\Build\vcvarsall.bat" amd64
+  set MSBuild="C:\Program Files (x86)\Microsoft Visual Studio\2017\Community\MSBuild\15.0\Bin\MSBuild.exe"
+  set backend=vs2017
+)
+
+if "%CUDA_PATH%"=="%CUDNN_PATH%" (
+  set CUDNN_LIB_PATH=%CUDNN_PATH%\lib\x64
+  set CUDNN_INCLUDE_PATH=%CUDNN_PATH%\include
+) else (
+  set CUDNN_LIB_PATH=%CUDA_PATH%\lib\x64,%CUDNN_PATH%\lib\x64
+  set CUDNN_INCLUDE_PATH=%CUDA_PATH%\include,%CUDNN_PATH%\include
+)
+
+if %CUDNN%==true set PATH=%CUDA_PATH%\bin;%PATH%
+
+meson build --backend %backend% --buildtype release -Ddx=%DX12% -Dcudnn=%CUDNN% -Dopencl=%OPENCL% ^
+-Dblas=true -Dmkl=%MKL% -Dopenblas=%OPENBLAS% -Deigen=%EIGEN% -Ddnnl=%DNNL% -Dgtest=%TEST% ^
+-Dcudnn_include="%CUDNN_INCLUDE_PATH%" -Dcudnn_libdirs="%CUDNN_LIB_PATH%" ^
+-Dmkl_include="%MKL_PATH%\include" -Dmkl_libdirs="%MKL_PATH%\lib\intel64" -Ddnnl_dir="%DNNL_PATH%" ^
+-Dopencl_libdirs="%OPENCL_LIB_PATH%" -Dopencl_include="%OPENCL_INCLUDE_PATH%" ^
+-Dopenblas_include="%OPENBLAS_PATH%\include" -Dopenblas_libdirs="%OPENBLAS_PATH%\lib" ^
+-Ddefault_library=static
+
+if errorlevel 1 exit /b
+
+pause
+
+cd build
+
+%MSBuild% /m /p:Configuration=Release /p:Platform=x64 /p:WholeProgramOptimization=true ^
+/p:PreferredToolArchitecture=x64 lc0.sln /filelogger

build-cuda-ninja.cmd

@@ -1,4 +1,71 @@
-v0.24.0-rc1 (2020-02-23)
+v0.25.0-rc1 (2020-04-09)
+~~~~~~~
+
+* Now requires a c++17 supporting compilation environment to build.
+* Support for Moves Left Head based networks. Includes options to adjust search
+  to favour shorter/longer wins/losses based on the moves left head output.
+* Mate score reporting is now possible, and move selection will prefer shorter
+  mates over longer ones when they are proven.
+* Training now outputs v5 format data. This passes the moves left information
+  back to training. This also includes support for multiple sub formats, 
+  including the existing standard, a new variant which can encode FRC960
+  castling, and also a further extension of that which tries to make training
+  data cannonical, so there aren't multiple positions that are trivially
+  equivalent with different network inputs.
+* Benchmark now includes a suite of 34 positions to test by default instead of
+  just start position.
+* Tensorflow backend works once more, almost just as hard to compile as it used
+  to be though.
+* `--noise` flag is gone, use `--noise-epsilon=0.25` to get the old behavior.
+* Some bug fixes related to drawscore.
+* Selfplay mode now defaults to the same value as match play for 
+  `--root-has-own-cpuct-params` (true).
+* Some advanced time management parameters are now accessed via the new 
+  `--time-manager` parameter instead of individual parameters.
+* Windows build script has been modernized.
+* Separate Eigen backend option for CPU.
+* Random backend no longer requires a network.
+* Random backend supports producing training data of any input format sub type.
+* Integer parameters now give better error messages when given invalid values.
+
+v0.24.1 (2020-03-15)
+~~~~~~~
+
+* Fix issues where logitq was being passed as drawscore and logitq wasn't 
+  passed to some GetQ calls. Causing major performance issues when either 
+  setting was non-default.
+
+v0.24.0 (2020-03-11)
+~~~~~~~
+
+* New parameter `--max-out-of-order-evals-factor` replaces 
+  `--max-out-of-order-evals` that was introduced in v0.24.0-rc3 and provides
+  the factor to multiply the maximum batch size to set maximum number
+  out-of-order evals per batch. The default value of 1.0 keeps the behavior
+  of previous releases.
+* Bug fix for hangs with very early stop command from non-conforming UCI hosts.
+
+v0.24.0-rc3 (2020-03-08)
+~~~~~~~~~~~
+
+* New parameter `--max-out-of-order-evals` to set maximum number out-of-order
+  evals per batch (was equal to the batch size before).
+* It's now possible to embed networks into the binary. It allows easier builds
+  of .apk for Android.
+* New parameter `--smart-pruning-minimum-batches` to only allow smart pruning
+  to stop after at least k batches, preventing insta-moves on slow backends.
+
+v0.24.0-rc2 (2020-03-01)
+~~~~~~~~~~~
+
+* All releases are now bundled with network id591226 (and the file date is old 
+  enough so it has a lower priority than networks that you already may have
+  in your directory).
+* Added a 'backendbench' mode to benchmark NN evaluation performance without
+  search.
+* Android builds are added to the official releases.
+
+v0.24.0-rc1 (2020-02-23)
 ~~~~~~~~~~~
 
 * Introduced DirectX12 backend.

build-cuda.cmd

@@ -1,13 +1,9 @@
 
-# Tested with Android NDK r18, default toolchain
+# Tested with Android NDK r19c, default toolchain
 # Targeting API level 21
 
-# Make the standalone toolchain
-# cd android-ndk-r18b/build/tools/
-# ./make_standalone_toolchain.py --arch arm64 --api 21 --stl libc++ --install-dir android-standalone-64
-
 # Set the toolchain path on your environment
-# export PATH="$HOME/.local/share/android-sdk/android-toolchains/android-standalone-64/bin:$PATH"
+# export PATH="$HOME/.local/share/android-sdk/ndk-bundle/toolchains/llvm/prebuilt/linux-x86_64/bin:$PATH"
 
 [host_machine]
 system = 'android'
@@ -19,8 +15,8 @@ endian = 'little'
 cpp_link_args = ['-llog', '-static-libstdc++']
 
 [binaries]
-c = 'aarch64-linux-android-clang'
-cpp = 'aarch64-linux-android-clang++'
+c = 'aarch64-linux-android21-clang'
+cpp = 'aarch64-linux-android21-clang++'
 ar = 'aarch64-linux-android-ar'
 strip = 'aarch64-linux-android-strip'
 ld = 'aarch64-linux-android-ld'