96b95a24ee
This adds updated Rust bindings that have been located at [nbigaouette/onnxruntime-rs](https://github.com/nbigaouette/onnxruntime-rs). check out the build instructions included in this PR at /rust/BUILD.md. Changes to the bindings included in this PR: - The bindings are generated with the build script on each build - The onnxruntime shared library is built with ORT_RUST_STRATEGY=compile which is now the default. - A memory leak was fixed where a call to free wasn't called - Several small memory errors were fixed - Session is Send but not Sync, Environment is Send + Sync - Inputs and Outputs can be ndarray::Arrays of many different types. Some commits can be squashed, if wanted, but were left unsquashed to show differences between old bindings and new bindings. This PR does not cover packaging nor does it include the Rust bindings withing the build system. For those of you who have previous Rust code based on the bindings, these new bindings can be used as a `path` dependency or a `git` dependency (though I have not tested this out). The work addressed in this PR was discussed in #11992 |
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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 | Inference | Training |
|---|---|---|
| Windows | ||
| Linux | ||
| Mac | ||
| Android | ||
| iOS | ||
| Web | ||
| Other |
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.