d433aa2459
* checkin transformers pipeline * add docker requirements * only trigger linux cpu * temp remove tf instalation due to numpy version conflicts * test numpy>=1.7 * revert numpy and disable transformers * add coloredlogs * enable shape_infer_helper and install transformers when needed * pip3? * testtest * enable more tets * line too long * remove pytorch1.4 test and added back some onnx files * add tests * copy dir * disable 2 teests * trim lines * add missing onnx * fix type * fix version conflicts * install psutil * change file path * mfix path * remove cached files * add back attention fusion test * labeled the shape infer test as slow * fix * enable tf2onnx test and enable pytest * refactor path * fix typo * add cwd |
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| include/onnxruntime/core | ||
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| onnxruntime | ||
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| tools | ||
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| build.amd64.1411.bat | ||
| build.bat | ||
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| CODEOWNERS | ||
| CONTRIBUTING.md | ||
| LICENSE | ||
| NuGet.config | ||
| ort.wprp | ||
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| README.md | ||
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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 | |||
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| 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.