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### Description <!-- Describe your changes. --> Add version for onnxruntime_providers_vitisai.dll. So, the onnxruntime_vitisai_ep.dll can check if the version is compatible. To make sure the old onnxruntime_vitisai_ep.dll still work, we would offset the api struct by version field. ### Motivation and Context <!-- - Why is this change required? What problem does it solve? --> This is the direct request from Microsoft. The following is the problem we try to solve: How would you describe the dependency between (a) onnxruntime_vitisai_ep.dll and (b) onnxruntime_providers_vitisai.dll? E.g. for each version of (a) there is a minimum required version of (b), or for each version of (b) there is minimum required version of (a). Please note that in practice we won't be able to use the exact version of ORT/EP that you tested against (because we might need to update ORT for other reasons), but we might be able to accommodate some version constraints that you specify. As we approach shipping, we'll lock the version of ORT/EP to allow for stabilization and more detailed testing (and work with you if it needs to be updated). |
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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 documentation 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
Builtin Pipeline Status
| System | Inference | Training |
|---|---|---|
| Windows | ||
| Linux | ||
| Mac | ||
| Android | ||
| iOS | ||
| Web | ||
| Other |
Third-party Pipeline Status
| System | Inference | Training |
|---|---|---|
| Linux |  |
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.