Build from Source

This project supports Python and can be built from source easily, or a simple cmake build without Python dependency.

Python package

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.
    OR 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.
  • run pytest test in the project root directory.

For a complete list of verified build configurations see here

Java package

Run bash ./ -DOCOS_BUILD_JAVA=ON to build jar package in out//Release folder

Android package

Use ./tools/android/ to build an Android AAR package.

iOS package

Use ./tools/ios/ 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.

The C++ shared library

for any other cases, please run build.bat or bash ./ 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$<$:Debug>"_ on running build.bat

check this link for source file copyright header.

Build ONNX Runtime with onnxruntime-extensions for Java package

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.

Tools required

  1. install visual studio 2022 (with cmake, git, desktop C++)
  2. install miniconda to have Python support (for onnxruntime build)
  3. OpenJDK: (OpenJDK 11.0.15 LTS)
  4. Gradle: (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-"
	# clone ONNXRuntime
	git clone -b rel-1.12.0 onnxruntime

	# clone onnxruntime-extensions
	git clone onnxruntime_extensions

	# build JAR package in this folder
	python ..\onnxruntime\tools\ci_build\ --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.

Python 3.8 3.9 3.10 3.11
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)