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* Make ORT as Pytorch JIT backend LORT likely doesn't work with aten fallback so we only test LORT in its own CI. * Revert changes to enable external CUDA allocator. Will add it later. Revert "Revert changes to enable external CUDA allocator. Will add it later." This reverts commit d5487f2e193014c805505afae8fb577c53667658. Fix external allocator * Relax tolerance and remove commented code * Print more information in CI * Fix pointer * Address comments. 1. Reuse ORT-eager mode's environment. 2. Remove unused ctor. * Use Pytorch master branch as all PRs are merged Fix * Refine based on cpplint feedbacks * Revert changes to allow custom CUDA allocator in public APIs * Use torch.testing.assert_close * Use unittest framework * Switch docker repo * Rename *.cpp to *.cc * Address comments * Add comment * Use same pipeline file for eager and lort pipelines * Address comments * Add yaml comment * Fix cmake files * Address comments * Rename flags, remove printing code, remove dead comment |
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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
General Information: onnxruntime.ai
Usage documention and tutorials: onnxruntime.ai/docs
Companion sample repositories:
- ONNX Runtime Inferencing: microsoft/onnxruntime-inference-examples
- ONNX Runtime Training: microsoft/onnxruntime-training-examples
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.