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* Update README.md * Update Versioning.md * Update rename_manylinux.sh Remove duplicate word * Update README.md Remove a 'the' as ONNX Runtime is a proper noun. * Update CUDA version to 9.1 cudnn version to 7.1 * Update ReleaseManagement.md * put tensorflow copy-right headers there are around 10 lines of code is borrowed from tflite. * Update README.md Mention C++ API * Update README.md Fix link * Update C_API.md Fix broken link to onnxruntime_c_api.h * Update ABI.md Delete mention of COM and fix 'ONNX Runtime' to be two words * Update README.md * Update README.md * Update C_API.md
136 lines
7.1 KiB
Markdown
136 lines
7.1 KiB
Markdown
# Build ONNX Runtime
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## Supported dev environments
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| OS | Supports CPU | Supports GPU| Notes |
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|-------------|:------------:|:------------:|------------------------------------|
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|Windows 10 | YES | YES |Must use VS 2017 or the latest VS2015|
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|Windows 10 <br/> Subsystem for Linux | YES | NO | |
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|Ubuntu 16.x | YES | YES | |
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|Ubuntu 17.x | YES | YES | |
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|Ubuntu 18.x | YES | YES | |
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|Fedora 24 | YES | YES | |
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|Fedora 25 | YES | YES | |
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|Fedora 26 | YES | YES | |
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|Fedora 27 | YES | YES | |
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|Fedora 28 | YES | NO |Cannot build GPU kernels but can run them |
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* Red Hat Enterprise Linux and CentOS are not supported.
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* GCC 4.x and below are not supported. If you are using GCC 7.0+, you'll need to upgrade eigen to a newer version before compiling ONNX Runtime.
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OS/Compiler Matrix:
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| OS/Compiler | Supports VC | Supports GCC | Supports Clang |
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|-------------|:------------:|:----------------:|:---------------:|
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|Windows 10 | YES | Not tested | Not tested |
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|Linux | NO | YES(gcc>=5.0) | YES |
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ONNX Runtime python binding only supports Python 3.x. Please use python 3.5+.
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## Build
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Install cmake-3.11 or better from https://cmake.org/download/.
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Checkout the source tree:
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```
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git clone --recursive https://github.com/Microsoft/onnxruntime
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cd onnxruntime
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./build.sh for Linux (or ./build.bat for Windows)
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```
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The build script runs all unit tests by default.
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The complete list of build options can be found by running `./build.sh (or ./build.bat) --help`
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## Build/Test Flavors for CI
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### CI Build Environments
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| Build Job Name | Environment | Dependency | Test Coverage | Scripts |
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|--------------------|---------------------|---------------------------------|--------------------------|------------------------------------------|
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| Linux_CI_Dev | Ubuntu 16.04 | python=3.5 | Unit tests; ONNXModelZoo | [script](tools/ci_build/github/linux/run_build.sh) |
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| Linux_CI_GPU_Dev | Ubuntu 16.04 | python=3.5; nvidia-docker | Unit tests; ONNXModelZoo | [script](tools/ci_build/github/linux/run_build.sh) |
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| Windows_CI_Dev | Windows Server 2016 | python=3.5 | Unit tests; ONNXModelZoo | [script](build.bat) |
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| Windows_CI_GPU_Dev | Windows Server 2016 | cuda=9.1; cudnn=7.1; python=3.5 | Unit tests; ONNXModelZoo | [script](build.bat) |
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## Additional Build Flavors
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The complete list of build flavors can be seen by running `./build.sh --help` or `./build.bat --help`. Here are some common flavors.
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### Windows CUDA Build
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ONNX Runtime supports CUDA builds. You will need to download and install [CUDA](https://developer.nvidia.com/cuda-toolkit) and [CUDNN](https://developer.nvidia.com/cudnn).
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ONNX Runtime is built and tested with CUDA 9.1 and CUDNN 7.1 using the Visual Studio 2017 14.11 toolset (i.e. Visual Studio 2017 v15.3).
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CUDA versions up to 9.2 and CUDNN version 7.1 should also work with versions of Visual Studio 2017 up to and including v15.7, however you may need to explicitly install and use the 14.11 toolset due to CUDA and CUDNN only being compatible with earlier versions of Visual Studio 2017.
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To install the Visual Studio 2017 14.11 toolset, see <https://blogs.msdn.microsoft.com/vcblog/2017/11/15/side-by-side-minor-version-msvc-toolsets-in-visual-studio-2017/>
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If using this toolset with a later version of Visual Studio 2017 you have two options:
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1. Setup the Visual Studio environment variables to point to the 14.11 toolset by running vcvarsall.bat prior to running cmake
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- e.g. if you have VS2017 Enterprise, an x64 build would use the following command
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`"C:\Program Files (x86)\Microsoft Visual Studio\2017\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" amd64 -vcvars_ver=14.11`
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2. Alternatively if you have CMake 3.12 or later you can specify the toolset version in the "-T" parameter by adding "version=14.11"
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- e.g. use the following with the below cmake command
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`-T version=14.11,host=x64`
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CMake should automatically find the CUDA installation. If it does not, or finds a different version to the one you wish to use, specify your root CUDA installation directory via the -DCUDA_TOOLKIT_ROOT_DIR CMake parameter.
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_Side note: If you have multiple versions of CUDA installed on a Windows machine and are building with Visual Studio, CMake will use the build files for the highest version of CUDA it finds in the BuildCustomization folder. e.g. C:\Program Files (x86)\Microsoft Visual Studio\2017\Enterprise\Common7\IDE\VC\VCTargets\BuildCustomizations\. If you want to build with an earlier version, you must temporarily remove the 'CUDA x.y.*' files for later versions from this directory._
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The path to the 'cuda' folder in the CUDNN installation must be provided. The 'cuda' folder should contain 'bin', 'include' and 'lib' directories.
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You can build with:
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```
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./build.sh --use_cuda --cudnn_home /usr --cuda_home /usr/local/cuda (Linux)
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./build.bat --use_cuda --cudnn_home <cudnn home path> --cuda_home <cuda home path> (Windows)
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```
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### MKL-DNN
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To build ONNX Runtime with MKL-DNN support, build it with `./build.sh --use_mkldnn --use_mklml`
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### OpenBLAS
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#### Windows
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Instructions how to build OpenBLAS for windows can be found here https://github.com/xianyi/OpenBLAS/wiki/How-to-use-OpenBLAS-in-Microsoft-Visual-Studio#build-openblas-for-universal-windows-platform.
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Once you have the OpenBLAS binaries, build ONNX Runtime with `./build.bat --use_openblas`
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#### Linux
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For Linux (e.g. Ubuntu 16.04), install libopenblas-dev package
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`sudo apt-get install libopenblas-dev` and build with `./build.sh --use_openblas`
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### OpenMP
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```
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./build.sh --use_openmp (for Linux)
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./build.bat --use_openmp (for Windows)
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```
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### Build with Docker on Linux
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Install Docker: `https://docs.docker.com/install/`
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#### CPU
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```
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cd tools/ci_build/github/linux/docker
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docker build -t onnxruntime_dev --build-arg OS_VERSION=16.04 -f Dockerfile.ubuntu .
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docker run --rm -it onnxruntime_dev /bin/bash
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```
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#### GPU
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If you need GPU support, please also install:
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1. nvidia driver. Before doing this please add 'nomodeset rd.driver.blacklist=nouveau' to your linux [kernel boot parameters](https://www.kernel.org/doc/html/v4.17/admin-guide/kernel-parameters.html).
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2. nvidia-docker2: [Install doc](`https://github.com/NVIDIA/nvidia-docker/wiki/Installation-(version-2.0)`)
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To test if your nvidia-docker works:
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```
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docker run --runtime=nvidia --rm nvidia/cuda nvidia-smi
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```
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Then build a docker image. We provided a sample for use:
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```
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cd tools/ci_build/github/linux/docker
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docker build -t cuda_dev -f Dockerfile.ubuntu_gpu .
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```
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Then run it
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```
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./tools/ci_build/github/linux/run_dockerbuild.sh
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```
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