ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
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Scott McKay fb4a8e12fc
Limit inclusion of Xamarin mobile target frameworks. (#9834)
- Only set them as targets for the ORT nuget package
    - Use OrtPackageId as the condition for inclusion, if installed
      - need to do the nuget restore via msbuild so that this property is set correctly
  - Add desktop-only version of the C# sln as there is no way to exclude the mobile specific csproj's from an sln
    - use this when applicable if someone is running build.py with the `--build_nuget` flag

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  - remove attempt to include symbols in the nuget package as nuget doesn't support symbols in native packages
  - update build.py to use `nuget` and not a windows specific path and filename for a linux build with `--build_nuget`
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setup.py Integrate TensorRT into GPU Python package (#9785) 2021-11-18 13:26:51 -08:00
ThirdPartyNotices.txt Clean up optional-lite references (#9534) 2021-10-25 21:05:45 -07:00
VERSION_NUMBER Bumping up to 1.10 (#9006) 2021-09-22 16:34:28 -07:00

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

General Information: onnxruntime.ai

Usage documention and tutorials: onnxruntime.ai/docs

Companion sample repositories:

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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.