7880342e5e
### Description * Add std::numeric_limits for MLFloat16 and BFloat16. * Update some comments in csharp ORTFloat16.shared.cs. * Add unit tests (including Clip) Note that the canonical NaN is not consistent in C++ and C#. C# uses negative quiet NaN as canonical NaN, while C++ uses positive quiet NaN. The choice of CSharp Float16.NaN is to be consistent with System.Half.NaN. FP16 data returns from CUDA might have 7FFF as NaN; FP16 data from CPU provider might have 0x7E00 as NaN. Anyway there is no consistent canonical NaN in ORT right now. Because all these NaNs are aligned with IEEE spec, there shall not an issue in downstream. ### Motivation and Context std::numeric_limits is used in codebase but not defined for MLFloat16 and BFloat16. It causes some bugs like https://github.com/microsoft/onnxruntime/issues/21957 introduced by https://github.com/microsoft/onnxruntime/pull/21493. |
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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 |
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| Windows | ||
| Linux | ||
| Mac | ||
| Android | ||
| iOS | ||
| Web | ||
| Other |
This project is tested with BrowserStack.
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.