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### Description Adds the ability for MIGraphX EP to save off or load compiled models to save time between inferences. Via Command line User should be able to set the save ability with ORT_MIGRAPHX_SAVE_COMPILED_MODEL ORT_MIGRAPHX_SAVE_COMPILE_PATH User should be able to set the load ability with ORT_MIGRAPHX_LOAD_COMPILED_MODEL ORT_MIGRAPHX_LOAD_COMPILE_PATH via Onnxruntime API migx_save_compiled_model migx_save_model_name migx_load_compiled_model migx_load_model_name ### Motivation and Context The motivation for this is to leverage MIGraphX's existing API to save/load models after our compile step of graph optimization. For larger models or models which were compiled with additional tuning steps, this saves time after first compile and inference run, and thus speeds up the user experience in order to encourage development. --------- Co-authored-by: Ted Themistokleous <tedthemistokleous@amd.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 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 |
|---|---|---|
| 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.