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ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
04900f96c1
## Description 1. Convert some git submodules to cmake external projects 2. Update nsync from [1.23.0](https://github.com/google/nsync/releases/tag/1.23.0) to [1.25.0](https://github.com/google/nsync/releases/tag/1.25.0) 3. Update re2 from 2021-06-01 to 2022-06-01 4. Update wil from an old commit to 1.0.220914.1 tag 5. Update gtest to a newer commit so that it can optionally leverage absl/re2 for parsing command line flags. The following git submodules are deleted: 1. FP16 2. safeint 3. XNNPACK 4. cxxopts 5. dlpack 7. flatbuffers 8. googlebenchmark 9. json 10. mimalloc 11. mp11 12. pthreadpool More will come. ## Motivation and Context There are 3 ways of integrating 3rd party C/C++ libraries into ONNX Runtime: 1. Install them to a system location, then use cmake's find_package module to locate them. 2. Use git submodules 6. Use cmake's external projects(externalproject_add). At first when this project was just started, we considered both option 2 and option 3. We preferred option 2 because: 1. It's easier to handle authentication. At first this project was not open source, and it had some other non-public dependencies. If we use git submodule, ADO will handle authentication smoothly. Otherwise we need to manually pass tokens around and be very careful on not exposing them in build logs. 2. At that time, cmake fetched dependencies after "cmake" finished generating vcprojects/makefiles. So it was very difficult to make cflags consistent. Since cmake 3.11, it has a new command: FetchContent, which fetches dependencies when it generates vcprojects/makefiles just before add_subdirectories, so the parent project's variables/settings can be easily passed to the child projects. And when the project went on, we had some new concerns: 1. As we started to have more and more EPs and build configs, the number of submodules grew quickly. For more developers, most ORT submodules are not relevant to them. They shouldn't need to download all of them. 2. It is impossible to let two different build configs use two different versions of the same dependency. For example, right now we have protobuf 3.18.3 in the submodules. Then every EP must use the same version. Whenever we have a need to upgrade protobuf, we need to coordinate across the whole team and many external developers. I can't manage it anymore. 3. Some projects want to manage the dependencies in a different way, either because of their preference or because of compliance requirements. For example, some Microsoft teams want to use vcpkg, but we don't want to force every user of onnxruntime using vcpkg. 7. Someone wants to dynamically link to protobuf, but our build script only does static link. 8. Hard to handle security vulnerabilities. For example, whenever protobuf has a security patch, we have a lot of things to do. But if we allowed people to build ORT with a different version of protobuf without changing ORT"s source code, the customer who build ORT from source will be able to act on such things in a quicker way. They will not need to wait ORT having a patch release. 9. Every time we do a release, github will also publish a source file zip file and a source file tarball for us. But they are not usable, because they miss submodules. ### New features After this change, users will be able to: 1. Build the dependencies in the way they want, then install them to somewhere(for example, /usr or a temp folder). 2. Or download the dependencies by using cmake commands from these dependencies official website 3. Similar to the above, but use your private mirrors to migrate supply chain risks. 4. Use different versions of the dependencies, as long as our source code is compatible with them. For example, you may use you can't use protobuf 3.20.x as they need code changes in ONNX Runtime. 6. Only download the things the current build needs. 10. Avoid building external dependencies again and again in every build. ### Breaking change The onnxruntime_PREFER_SYSTEM_LIB build option is removed you could think from now it is default ON. If you don't like the new behavior, you can set FETCHCONTENT_TRY_FIND_PACKAGE_MODE to NEVER. Besides, for who relied on the onnxruntime_PREFER_SYSTEM_LIB build option, please be aware that this PR will change find_package calls from Module mode to Config mode. For example, in the past if you have installed protobuf from apt-get from ubuntu 20.04's official repo, find_package can find it and use it. But after this PR, it won't. This is because that protobuf version provided by Ubuntu 20.04 is too old to support the "config mode". It can be resolved by getting a newer version of protobuf from somewhere. |
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ONNX Runtime is a cross-platform inference and training machine-learning accelerator.
ONNX Runtime inference can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms. Learn more →
ONNX Runtime training can accelerate the model training time on multi-node NVIDIA GPUs for transformer models with a one-line addition for existing PyTorch training scripts. Learn more →
Get Started & Resources
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General Information: onnxruntime.ai
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Usage documention and tutorials: onnxruntime.ai/docs
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YouTube video tutorials: youtube.com/@ONNXRuntime
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Companion sample repositories:
- ONNX Runtime Inferencing: microsoft/onnxruntime-inference-examples
- ONNX Runtime Training: microsoft/onnxruntime-training-examples
Build Pipeline Status
| System | CPU | GPU | EPs |
|---|---|---|---|
| Windows | |||
| Linux | |||
| Mac | |||
| Android | |||
| iOS | |||
| WebAssembly |
Data/Telemetry
Windows distributions of this project may collect usage data and send it to Microsoft to help improve our products and services. See the privacy statement for more details.
Contributions and Feedback
We welcome contributions! Please see the contribution guidelines.
For feature requests or bug reports, please file a GitHub Issue.
For general discussion or questions, please use GitHub Discussions.
Code of Conduct
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
License
This project is licensed under the MIT License.