This project supports Python and can be built from source easily, or a simple cmake build without Python dependency.
The package contains all custom operators and some Python scripts to manipulate the ONNX models.
- Install Visual Studio with C++ development tools on Windows, or gcc(>8.0) for Linux or xcode for macOS, and cmake on the unix-like platform. (hints: in Windows platform, if cmake bundled in Visual Studio was used, please specify the set VSDEVCMD=%ProgramFiles(x86)%\Microsoft Visual Studio<VERSION_YEAR><Edition>\Common7\Tools\VsDevCmd.bat)
- If running on Windows, ensure that long file names are enabled, both for the operating system and for git:
git config --system core.longpaths true
- Prepare Python env and install the pip packages in the requirements.txt.
pip install .to build and install the package.
pip install -e .to install the package in the development mode, which is more friendly for the developer since the Python code change will take effect without having to copy the files to a different location in the disk.(hints: debug=1 in setup.cfg wil make C++ code be debuggable in a Python process.)
- ‘pip install -r requirements-dev.txt’ to install pip packages for development.
pytest testin the project root directory.
For a complete list of verified build configurations see here
bash ./build.sh -DOCOS_BUILD_JAVA=ON to build jar package in out/
- pre-requisites: Android Studio
./tools/android/build_aar.py to build an Android AAR package.
./tools/ios/build_xcframework.py to build an iOS xcframework package.
ONNXRuntime-Extensions will be built as a static library and linked with ONNXRuntime due to the lack of a good dynamic linking mechanism in WASM. Here are two additional arguments –-use_extensions and –extensions_overridden_path on building onnxruntime to include ONNXRuntime-Extensions footprint in the ONNXRuntime package.
for any other cases, please run
bash ./build.sh to build the library. By default, the DLL or the library will be generated in the directory
out/<OS>/<FLAVOR>. There is a unit test to help verify the build.
VC Runtime static linkage If you want to build the binary with VC Runtime static linkage, please add a parameter _-DCMAKE_MSVC_RUNTIME_LIBRARY=”MultiThreaded$<$
check this link https://docs.opensource.microsoft.com/releasing/general-guidance/copyright-headers/ for source file copyright header.
The following step are demonstrated for Windows Platform only, the others like Linux and MacOS can be done similarly.
Android build was supported as well; check here for arguments to build AAR package.
- install visual studio 2022 (with cmake, git, desktop C++)
- install miniconda to have Python support (for onnxruntime build)
- OpenJDK: https://docs.microsoft.com/en-us/java/openjdk/download (OpenJDK 11.0.15 LTS)
- Gradle: https://gradle.org/releases/ (v6.9.2)
Launch Developer PowerShell for VS 2022 in Windows Tereminal
. $home\miniconda3\shell\condabin\conda-hook.ps1 conda activate base $env:JAVA_HOME="C:\Program Files\Microsoft\jdk-22.214.171.124-hotspot" # clone ONNXRuntime git clone -b rel-1.12.0 https://github.com/microsoft/onnxruntime.git onnxruntime # clone onnxruntime-extensions git clone https://github.com/microsoft/onnxruntime-extensions.git onnxruntime_extensions # build JAR package in this folder mkdir ortall.build cd ortall.build python ..\onnxruntime\tools\ci_build\build.py --config Release --cmake_generator "Visual Studio 17 2022" --build_java --build_dir . --use_extensions --extensions_overridden_path "..\onnxruntime-extensions"
The matrix below lists the versions of individual dependencies of onnxruntime-extensions. These are the configurations that are routinely and extensively verified by our CI.
|Onnxruntime||1.12.1 (Aug 4, 2022)||1.13.1(Oct 24, 2022)||1.14.1 (Mar 2, 2023)||1.15.0 (May 24, 2023)|