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### Description Unlike most ORT classes `SessionOptions` and `RunOptions` don't trigger native library loading of the JNI binding and ORT when the classes are initialized (after class loading). This was initially because I thought that loading an inner class would trigger the static initialization of the outer class, but this is not true. So if you create a `SessionOptions` instance before referencing `OrtEnvironment` then you won't trigger library loading and you'll get an error saying it couldn't link the native method that creates a `SessionOptions` object. Note this doesn't prevent users from creating a `SessionOptions` and modifying it before the `OrtEnvironment` is created, which can still cause issues. It would be a breaking API change to modify the `SessionOptions` constructor to take an environment, and it wouldn't mirror the way it works in the C API which requires this by convention rather than API design, but we can discuss making that modification later. ### Motivation and Context Reduces the occurrence of mysterious Java library loading errors. Helps with #16434. |
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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.