47435311f4
* Include pytorch_export_contrib_ops in inference builds Rename / move it from tools/python/register_custom_ops_pytorch_exporter to onnxruntime/python/tools/pytorch_export_contrib_ops. Rationale for inclusion in inference builds: This code is potentially useful for anyone using ORT, not just training. Rationale for new name: "Contrib op" is the nomenclature used within ORT to refer to the set of ops that are not in the standard op set but are included by default with ORT. This is more specific than "custom op", which is what the PyTorch exporter uses to refer to any non-standard op. Step 1 of addressing #8818. After this is merged I will update the docs. * Enable test_pytorch_export_contrib_ops.py in CI Fixes AB#1342330 |
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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 | |||
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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.