- # build support status
- ## host build
- * windows build (cpu + gpu)
- * linux build (cpu + gpu)
- * macos build (cpu only)
- ## cross build
- * windows cross build arm-android (ok)
- * windows cross build arm-linux (ok)
- * linux cross build arm-android (ok)
- * linux cross build arm-linux (ok)
- * macos cross build arm-android (ok)
- * macos cross build arm-linux (ok but experimental)
- * macos cross build ios (ok)
-
- # build env prepare
- ## package install
- ### windows host build
- ```
- 1: installl Visual Studio (need support LLVM/clang-cl), eg 2019
- pls install LLVM-10, VS llvm linker have issue, pls replace lld-link.exe,
- download from https://releases.llvm.org/download.html#10.0.0
- 2: install extension of VS: python/cmake/LLVM
- 3: CUDA env(if enable CUDA), version detail: project_root_dir/README.md
- 4: now we support cuda10.1+cudnn7.6+TensorRT6.0 on windows, as windows can
- only use dll in fact with cudnn/TensorRT, so please install the same version;
- 4a: install cuda10.1 to C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1
- 4b: install cudnn7.6 to C:\Program Files\NVIDIA GPU Computing Toolkit\cudnn-10.1-windows10-x64-v7.6.5.32
- 4c: install TensorRT6.0 to C:\Program Files\NVIDIA GPU Computing Toolkit\TensorRT-6.0.1.5
- 4d: add C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\bin to system Path env
- 4e: add C:\Program Files\NVIDIA GPU Computing Toolkit\cudnn-10.1-windows10-x64-v7.6.5.32\cuda\bin to system Path env
- 4f: add C:\Program Files\NVIDIA GPU Computing Toolkit\TensorRT-6.0.1.5\lib Path
- if u do not do 4d/4e/4f, CUDA runtime can not find dll
- 5: install python3 (DFT 3.8.3) to /c/Users/${USER}/mge_whl_python_env/3.8.3 and
- put it to PATH env and run python3 -m pip install numpy (if u want to build with training mode or build python whl)
- ```
- ### linux host build
- ```
- 1: cmake, which version > 3.15.2
- 2: gcc/g++, which version > 6, (gcc/g++ >= 7, if need build training)
- 3: install build-essential git git-lfs gfortran libgfortran-6-dev autoconf gnupg flex bison gperf curl
- 4: zlib1g-dev gcc-multilib g++-multilib lib32ncurses5-dev libxml2-utils xsltproc unzip libtool:
- 5: librdmacm-dev rdmacm-utils python3-dev swig python3-numpy texinfo
- 6: CUDA env(if enable CUDA), version detail: project_root_dir/README.md
- ```
- ### macos host build
- ```
- 1: cmake, which version > 3.15.2
- 2: install brew: /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install.sh)"
- 3: brew install python python3 swig coreutils
- 4: install at least xcode command line tool: https://developer.apple.com/xcode/
- 5: about cuda: we do not support CUDA on macos
- 6: python3 -m pip install numpy (if u want to build with training mode or build python whl)
- ```
- ### cross build for arm-android
- now we support windows/linux/macos cross build to arm-android
- ```
- 1: install unix-like tools, eg MSYS if you are using windows(recommend)
- we also support CMD.exe or powershell on windows
- 1: download NDK from https://developer.android.google.cn/ndk/downloads/
- for diff OS platform package, suggested NDK20 or NDK21
- 2: export NDK_ROOT=NDK_DIR at bash-like env
- 3: config NDK_ROOT to PATH env at windows control board if use CMD/powershell
- ```
- ### cross build for arm-linux
- now we support arm-linux on linux and windows fully, also experimental on MACOS
- ```
- 1: download toolchains on https://releases.linaro.org/components/toolchain/gcc-linaro/
- or https://developer.arm.com/tools-and-software/open-source-software/developer-tools/gnu-toolchain/gnu-a/downloads
- if use windows or linux
- 2: download https://github.com/thinkski/osx-arm-linux-toolchains if use MACOS
- ```
- ### cross build for ios
- now we only support cross build to ios on MACOS
- ```
- 1: install full xcode: https://developer.apple.com/xcode/
- ```
- ## third-party code prepare
- ### with bash env(linux/macos/unix-like tools on windows, eg: msys etc)
- ```
- ./third_party/prepare.sh
- ./third_party/install-mkl.sh
- ```
- ### windows shell env(eg: cmd, powershell etc)
- infact if you can use git command on windows, which means you always install
- bash.exe at the same dir of git.exe, find it, then you can prepare third-party
- code by command:
- ```
- bash.exe ./third_party/prepare.sh
- bash.exe ./third_party/install-mkl.sh
- ```
- # how to build
- ## with bash env(linux/macos/unix-like tools on windows, eg: msys etc)
- ```
- 1: host build just use scripts:scripts/cmake-build/host_build.sh
- 2: cross build to arm-android: scripts/cmake-build/cross_build_android_arm_inference.sh
- 3: cross build to arm-linux: scripts/cmake-build/cross_build_linux_arm_inference.sh
- 4: cross build to ios: scripts/cmake-build/cross_build_ios_arm_inference.sh
- ```
- ## windows shell env(eg: cmd, powershell etc)
- ```
- 1: we do not provide BAT for cmd/powershlel scripts, BUT u can refs for scripts/cmake-build/*.sh
- ```
- ## Visual Studio GUI(only for windows host)
- ```
- 1: import megengine src to Visual Studio as a project
- 2: right click CMakeLists.txt, choose config 'cmake config'
- choose clang_cl_x86 or clang_cl_x64
- 3: config other CMAKE config, eg, CUDA ON OR OFF
- ```
-
-
- # other arm-linux-like board support
- it`s easy to support other customized arm-linux-like board, example:
- 1: HISI 3516/3519, infact u can just use toolchains from arm developer or linaro
- then call scripts/cmake-build/cross_build_linux_arm_inference.sh to build a ELF
- binary, or if you get HISI official toolschain, you just need modify CMAKE_CXX_COMPILER
- and CMAKE_C_COMPILER in toolchains/arm-linux-gnueabi* to a real name
-
- 2: about Raspberry, just use scripts/cmake-build/cross_build_linux_arm_inference.sh
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