91075255a7
* prepare for C# to configure provider options * add c# code * revert modification * Add update provider info configuration in trt ep side * fix bugs * fix bug for compiler error C2259 * Add c# test * fix bug * fix bug * Properly deal with string * Add c# api for accepting trt provider options * fix bug * Modify C# test * add shared lib test * Add get provider options functionality * clean up * clean up * fix bug * fix bugs for CI * Fix bugs for CI and documentation * Move TRT EP provider options related functions out of C API * revert * fix bug * refactor * add check for provider options string * code refactor * fix CI bug * Fix CI bugs * clean up * fix bug * Fix bug for Post Analysis * fix accidental bug * Add API_IMPL_BEGIN/API_IMPL_END * clean up * code refactor * code refactor * fix CI fail * fix bug * use string append * Change the code to better handle strncpy and string append |
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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
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.