5b492cbae3
Integrate TensorRT 8.5 - Update TensorRT EP to support TensorRT 8.5 - Update relevant CI pipelines - Disable known non-supported ops for TensorRT - Make timeout configurable. We observe more than [20 hours](https://aiinfra.visualstudio.com/Lotus/_build/results?buildId=256729&view=logs&j=71ce39d8-054f-502a-dcd0-e89fa9931f40) of running unit tests with TensorRT 8.5 in package pipelines. Because we can't use placeholder to significantly reduce testing time (c-api application test will deadlock) in package pipelines, we only run subsets of model tests and unit tests that are related to TRT (add new build flag--test_all_timeout and set it to 72000 seconds by package pipelines). Just to remember, we still run all the tests in TensorRT CI pipelines to have full test coverage. - include https://github.com/microsoft/onnxruntime/pull/13918 to fix onnx-tensorrt compile error. Co-authored-by: George Wu <jywu@microsoft.com> |
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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
Build Pipeline Status
| System | CPU | GPU | EPs |
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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.