ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
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Vrajang Parikh 67f4a4fd16
Objective-C binding for ORT training (#16127)
### Description
Implement Objective-C binding for `ORTCheckPoint`. Additionally, 
- Modify `onnxruntime_objectivec.cmake` to only include training header
and sources when training flag is enabled
- Enable objective-c binding for `orttraining-mac-ci-pipeline`

### Motivation and Context
This PR is part of implementing Objective-C bindings for training API.
It implements objective-c binding for ORTCheckPoint class. The
objective-C API closely resembles the C++ API.

**Note**: The test for saving checkpoint is skipped as it requires use
of training session. It will be added when the objective-c binding for
`ORTTrainingSession` is added.
2023-06-07 14:01:30 -07:00
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cmake Objective-C binding for ORT training (#16127) 2023-06-07 14:01:30 -07:00
csharp Introduce float 8 types (#14731) 2023-05-30 13:25:58 -07:00
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java Fixing CoreML in Java (#16231) 2023-06-07 12:24:57 -07:00
js [WebNN EP] Merge support for segment anything into main branch (#16208) 2023-06-07 09:56:37 -07:00
objectivec Objective-C binding for ORT training (#16127) 2023-06-07 14:01:30 -07:00
onnxruntime Fix some build issues on MacOS with Xcode 14.3. (#15878) 2023-06-07 12:07:11 -07:00
orttraining Detect fake tensor mode if it has already been created. (#16220) 2023-06-02 23:17:49 -07:00
rust Add rust bindings (#12606) 2023-02-08 14:57:15 -08:00
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swift/OnnxRuntimeBindingsTests Add iOS Swift Package Manager support (#15297) 2023-04-20 16:18:35 +10:00
tools Objective-C binding for ORT training (#16127) 2023-06-07 14:01:30 -07:00
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Package.swift Add iOS Swift Package Manager support (#15297) 2023-04-20 16:18:35 +10:00
packages.config [DML EP] Update DirectML version to 1.12.0 (#16011) 2023-05-18 19:37:12 -07:00
pyproject.toml Bump ruff in CI (#15533) 2023-04-17 10:11:44 -07:00
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requirements-dev.txt Remove codecov from requirements-dev.txt (#15487) 2023-04-12 18:48:02 -07:00
requirements-doc.txt
requirements-lintrunner.txt Enable RUFF as a formatter (#15699) 2023-04-26 14:04:07 -07:00
requirements-training.txt Remove protobuf pin from training requirements (#13695) 2022-11-22 12:27:18 -08:00
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setup.py Fix python pipeline for AzureEP without using root (#16023) 2023-05-22 16:38:47 -07:00
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VERSION_NUMBER Update VERSION_NUMBER (#15773) 2023-05-03 15:07:34 -07:00

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

Builtin Pipeline Status

System Inference Training
Windows Build Status
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Mac Build Status
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Third-party Pipeline Status

System Inference Training
Linux Build Status

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.