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### Description 1. Update donwload-artifacts to flex-downloadartifacts to make it eaiser to debug. 2. Move the native files into Gpu.Windows and Gpu-linux packages. Onnxruntime-Gpu has dependency on them. 3. update the package validation as well 4. Add 2 stages to run E2E test for GPU.Windows and GPU.Linux for example:  ### Motivation and Context Single Onnxruntime.Gpu Package size has already excceded the Nuget size limit. We split the package into some smaller packages to make them can be published. For compatibility, the user can install or upgrade Onnxruntime.Gpu, which will install Gpu.Windows and Gpu.Linux automatically. And the user can only install Gpu.Windows and Gpu.Linux directly. ### Test Link 1. In ORT_NIGHTLY 2. Install the preview version in nuget-int. (nuget source: https://apiint.nugettest.org/v3/index.json) --------- Co-authored-by: Scott McKay <skottmckay@gmail.com> |
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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
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.