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onnx
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Description

Open standard for machine learning interoperability

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Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models, both deep learning and traditional ML. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types. Currently we focus on the capabilities needed for inferencing (scoring).

ONNX is widely supported and can be found in many frameworks, tools, and hardware. Enabling interoperability between different frameworks and streamlining the path from research to production helps increase the speed of innovation in the AI community. We invite the community to join us and further evolve ONNX.

Use ONNX

Learn about the ONNX spec

Programming utilities for working with ONNX Graphs

Contribute

ONNX is a community project. We encourage you to join the effort and contribute feedback, ideas, and code. You can participate in the SIGs and Working Groups to shape the future of ONNX.

Check out our contribution guide to get started.

If you think some operator should be added to ONNX specification, please read this document.

Discuss

We encourage you to open Issues, or use Slack for more real-time discussion

Follow Us

Stay up to date with the latest ONNX news. [Facebook] [Twitter]

Installation

Prerequisites

numpy >= 1.16.6
protobuf >= 3.12.2
six
typing-extensions >= 3.6.2.1

Official Python packages

ONNX released packages are published in PyPi.

pip install numpy protobuf==3.16.0
pip install onnx

Weekly packages are published in test pypi to enable experimentation and early testing.

Conda packages

A binary build of ONNX is available from Conda, in conda-forge:

conda install -c conda-forge numpy protobuf==3.16.0 libprotobuf=3.16.0
conda install -c conda-forge onnx

You can also use the onnx-dev docker image for a Linux-based installation without having to worry about dependency versioning.

Build ONNX from Source

Before building from source uninstall any existing versions of onnx

pip uninstall onnx
.

Generally spreaking, you need to install protobuf C/C++ libraires and tools before proceeding forward. Then depending on how you installed protobuf, you need to set environment variable CMAKEARGS to "-DONNXUSEPROTOBUFSHAREDLIBS=ON" or "-DONNXUSEPROTOBUFSHARED_LIBS=OFF". For example, you may need to run the following command:

Linux:

bash
export CMAKE_ARGS="-DONNX_USE_PROTOBUF_SHARED_LIBS=ON"
Windows:
bat
set CMAKE_ARGS="-DONNX_USE_PROTOBUF_SHARED_LIBS=ON"

The ON/OFF depends on what kind of protobuf library you have. Shared libraries are files ending with *.dll/*.so/*.dylib. Static libraries are files ending with *.a/*.lib. This option depends on how you get your protobuf library and how it was built. And it is default OFF. You don't need to run the commands above if you'd prefer to use a static protobuf library.

Windows

If you are building ONNX from source, it is recommended that you also build Protobuf locally as a static library. The version distributed with conda-forge is a DLL, but ONNX expects it to be a static library. Building protobuf locally also lets you control the verison of protobuf. The tested and recommended version is 3.16.0.

The instructions in this README assume you are using Visual Studio. It is recommended that you run all the commands from a shell started from "x64 Native Tools Command Prompt for VS 2019" and keep the build system generator for cmake (e.g., cmake -G "Visual Studio 16 2019") consistent while building protobuf as well as ONNX.

You can get protobuf by running the following commands:

bat
git clone https://github.com/protocolbuffers/protobuf.git
cd protobuf
git checkout v3.16.0
cd cmake
cmake -G "Visual Studio 16 2019" -A x64 -DCMAKE_INSTALL_PREFIX= -Dprotobuf_MSVC_STATIC_RUNTIME=ON -Dprotobuf_BUILD_SHARED_LIBS=OFF -Dprotobuf_BUILD_TESTS=OFF -Dprotobuf_BUILD_EXAMPLES=OFF .
msbuild protobuf.sln /m /p:Configuration=Release
msbuild INSTALL.vcxproj /p:Configuration=Release
Then it will be built as a static library and installed to . Please add the bin directory(which contains protoc.exe) to your PATH.
set PATH=/bin;%PATH%

Please note: if your protobuginstalldir contains spaces, do not add quotation marks around it.

Alternative: if you don't want to change your PATH, you can set ONNXPROTOCEXECUTABLE instead.

bat
set CMAKE_ARGS=-DONNX_PROTOC_EXECUTABLE=

Then you can build ONNX as: ``` git clone https://github.com/onnx/onnx.git cd onnx git submodule update --init --recursive

prefer lite proto

set CMAKEARGS=-DONNXUSELITEPROTO=ON pip install -e . ```

Linux

First, you need to install protobuf.

Ubuntu users: the quickest way to install protobuf is to run

apt-get install python3-pip python3-dev libprotobuf-dev protobuf-compiler

Then you can build ONNX as: ``` export CMAKEARGS="-DONNXUSEPROTOBUFSHARED_LIBS=ON" git clone --recursive https://github.com/onnx/onnx.git cd onnx

prefer lite proto

set CMAKEARGS=-DONNXUSELITEPROTO=ON pip install -e . ```

Otherwise, you may need to install it from source. You can use the following commands to do it:

Debian/Ubuntu:

git clone https://github.com/protocolbuffers/protobuf.git
cd protobuf
git checkout v3.16.0
git submodule update --init --recursive
mkdir build_source && cd build_source
cmake ../cmake -Dprotobuf_BUILD_SHARED_LIBS=OFF -DCMAKE_INSTALL_PREFIX=/usr -DCMAKE_INSTALL_SYSCONFDIR=/etc -DCMAKE_POSITION_INDEPENDENT_CODE=ON -Dprotobuf_BUILD_TESTS=OFF -DCMAKE_BUILD_TYPE=Release
make -j$(nproc)
make install

CentOS/RHEL/Fedora:

git clone https://github.com/protocolbuffers/protobuf.git
cd protobuf
git checkout v3.16.0
git submodule update --init --recursive
mkdir build_source && cd build_source
cmake ../cmake  -DCMAKE_INSTALL_LIBDIR=lib64 -Dprotobuf_BUILD_SHARED_LIBS=OFF -DCMAKE_INSTALL_PREFIX=/usr -DCMAKE_INSTALL_SYSCONFDIR=/etc -DCMAKE_POSITION_INDEPENDENT_CODE=ON -Dprotobuf_BUILD_TESTS=OFF -DCMAKE_BUILD_TYPE=Release
make -j$(nproc)
make install

Here "-DCMAKEPOSITIONINDEPENDENT_CODE=ON" is crucial. By default static libraries are built without "-fPIC" flag, they are not position independent code. But shared libraries must be position independent code. Python C/C++ extensions(like ONNX) are shared libraries. So if a static library was not built with "-fPIC", it can't be linked to such a shared library.

Once build is successful, update PATH to include protobuf paths.

Then you can build ONNX as: ``` git clone https://github.com/onnx/onnx.git cd onnx git submodule update --init --recursive

prefer lite proto

set CMAKEARGS=-DONNXUSELITEPROTO=ON pip install -e . ```

  • Mac
    export NUM_CORES=`sysctl -n hw.ncpu`
    brew update
    brew install autoconf && brew install automake
    wget https://github.com/protocolbuffers/protobuf/releases/download/v3.16.0/protobuf-cpp-3.16.0.tar.gz
    tar -xvf protobuf-cpp-3.16.0.tar.gz
    cd protobuf-3.16.0
    mkdir build_source && cd build_source
    cmake ../cmake -Dprotobuf_BUILD_SHARED_LIBS=OFF -DCMAKE_POSITION_INDEPENDENT_CODE=ON -Dprotobuf_BUILD_TESTS=OFF -DCMAKE_BUILD_TYPE=Release
    make -j${NUM_CORES}
    make install
    

Once build is successful, update PATH to include protobuf paths.

Then you can build ONNX as: ``` git clone --recursive https://github.com/onnx/onnx.git cd onnx

prefer lite proto

set CMAKEARGS=-DONNXUSELITEPROTO=ON pip install -e . ```

Verify Installation

After installation, run

python -c "import onnx"

to verify it works.

Common Build Options

For full list refer to CMakeLists.txt
Environment variables
*

USE_MSVC_STATIC_RUNTIME
should be 1 or 0, not ON or OFF. When set to 1 onnx links statically to runtime library.
Default: USEMSVCSTATIC_RUNTIME=1
  • DEBUG
    should be 0 or 1. When set to 1 onnx is built in debug mode. or debug versions of the dependencies, you need to open the CMakeLists file and append a letter
    d
    at the end of the package name lines. For example,
    NAMES protobuf-lite
    would become
    NAMES protobuf-lited
    .
    Default: Debug=0

CMake variables *

ONNX_USE_PROTOBUF_SHARED_LIBS
should be ON or OFF.
Default: ONNXUSEPROTOBUFSHAREDLIBS=OFF USEMSVCSTATICRUNTIME=1
`ONNX
USEPROTOBUFSHAREDLIBS` determines how onnx links to protobuf libraries.
- When set to ON - onnx will dynamically link to protobuf shared libs, PROTOBUF
USEDLLS will be defined as described here, ProtobufUSESTATICLIBS will be set to OFF and
USE_MSVC_STATIC_RUNTIME
must be 0.
- When set to OFF - onnx will link statically to protobuf, and ProtobufUSESTATICLIBS will be set to ON (to force the use of the static libraries) and `USEMSVCSTATICRUNTIME` can be 0 or 1.
  • ONNX_USE_LITE_PROTO
    should be ON or OFF. When set to ON onnx uses lite protobuf instead of full protobuf.
    Default: ONNXUSELITE_PROTO=OFF
  • ONNX_WERROR
    should be ON or OFF. When set to ON warnings are treated as errors.
    Default: ONNX_WERROR=OFF in local builds, ON in CI and release pipelines.

Common Errors

  • Note: the

    import onnx
    command does not work from the source checkout directory; in this case you'll see
    ModuleNotFoundError: No module named 'onnx.onnx_cpp2py_export'
    . Change into another directory to fix this error.
  • Building ONNX on Ubuntu works well, but on CentOS/RHEL and other ManyLinux systems, you might need to open the CMakeLists file and replace all instances of

    /lib
    with
    /lib64
    .

Testing

ONNX uses pytest as test driver. In order to run tests, you will first need to install pytest:

pip install pytest nbval

After installing pytest, use the following command to run tests.

pytest

Development

Check out the contributor guide for instructions.

License

Apache License v2.0

Code of Conduct

ONNX Open Source Code of Conduct

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