ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
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Adam Pocock 03c3e91b0d
[java] Relaxing CoreML test (#16777)
### Description
Reduces precision on the CoreML provider test as it returns slightly
different answers than the other tested providers. Checked on a 2020 13"
M1 MBP.

### Motivation and Context
Fixes Java CoreML test failure after #16763.
2023-08-09 11:43:05 -07:00
.config Update tsaoptions.json: update the email alias (#13448) 2022-10-26 15:56:16 -07:00
.devcontainer Remove two lines in the Dockerfile for Github Codespace (#12278) 2022-07-21 20:52:17 -07:00
.gdn Update win-ci-pipeline.yml: enable xnnpack tests (#16244) 2023-06-14 19:12:42 -07:00
.github Fix onnxruntime_tvm (#16933) 2023-08-02 07:51:00 +08:00
.pipelines Workaround to upgrade VS2022 for Windows ARM build (#16826) 2023-07-25 08:35:52 +08:00
.vscode Broadcasting for SLN for CPU and CUDA (#16510) 2023-08-07 09:55:42 -07:00
cgmanifests [TensorRT EP] TRT 8.6 minor version update (#16475) 2023-06-26 10:44:27 -07:00
cmake Fix FunctionProto visualization (#17063) 2023-08-09 11:05:52 -07:00
csharp RunAsync in C# (#16890) 2023-08-07 22:19:38 -07:00
dockerfiles Enable model subgraph execution in OVEP and setting the OpenVINO dll's to the path from the OpenVINO pypi packge in OVEP and fix OVEP windows io buffer sample (#16147) 2023-06-16 19:47:09 -07:00
docs Use full qualified name for PythonOp export (#17021) 2023-08-09 10:58:33 +08:00
include/onnxruntime/core Add API for updating CUDA EP provider option user compute stream (#17037) 2023-08-09 09:24:19 -07:00
java [java] Relaxing CoreML test (#16777) 2023-08-09 11:43:05 -07:00
js [js/web] enable webgpu in browser unit test (#16310) 2023-08-08 11:45:04 -07:00
objectivec Objective-C Add Support to Create and Query String ORTValues (#16764) 2023-07-20 17:39:29 -07:00
onnxruntime Add API for updating CUDA EP provider option user compute stream (#17037) 2023-08-09 09:24:19 -07:00
orttraining [CUDA][ROCm] Allow allocating ScratchBuffer from TuningContext (#17028) 2023-08-10 00:05:10 +08:00
rust Add rust bindings (#12606) 2023-02-08 14:57:15 -08:00
samples Enable pylint and numpy rules (#15218) 2023-03-27 20:37:53 -07:00
swift/OnnxRuntimeBindingsTests Add iOS Swift Package Manager support (#15297) 2023-04-20 16:18:35 +10:00
tools [js/web] enable webgpu in browser unit test (#16310) 2023-08-08 11:45:04 -07:00
winml Format c++ code under winml/ (#16660) 2023-07-25 21:56:50 -07:00
.clang-format Run clang-format in CI (#15524) 2023-04-18 09:26:58 -07:00
.clang-tidy Create clang-tidy CI (#12653) 2022-09-30 08:05:38 -07:00
.dockerignore
.gitattributes
.gitignore remove 'lib/' from .gitignore (#15613) 2023-04-24 18:43:32 -07:00
.gitmodules Update eigen to 3.4 and remove the eigen from git submodule (#15875) 2023-05-11 11:56:59 -07:00
.lintrunner.toml Format c++ code under winml/ (#16660) 2023-07-25 21:56:50 -07:00
build.bat Upgrade old Python version in packaging pipeline (#16667) 2023-07-17 08:24:47 -07:00
build.sh Upgrade old Python version in packaging pipeline (#16667) 2023-07-17 08:24:47 -07:00
CITATION.cff
CODEOWNERS Add owners for public facing API files (#15288) 2023-03-30 17:16:15 -07:00
CONTRIBUTING.md Fix link to High Level Design (#11786) 2023-02-28 11:05:54 -08:00
lgtm.yml Fix lgtm C++ error (#13613) 2022-11-10 10:06:22 -08:00
LICENSE
NuGet.config
ort.wprp
ORT_icon_for_light_bg.png
Package.swift Objective-C Add Support to Create and Query String ORTValues (#16764) 2023-07-20 17:39:29 -07:00
packages.config [DML EP] Update DirectML version to 1.12.0 (#16011) 2023-05-18 19:37:12 -07:00
pyproject.toml Updating QDQ to support Float8E4M3FN (#16550) 2023-08-08 12:18:48 +02:00
README.md add third-party pipeline status to README.md (#16155) 2023-05-31 22:14:39 -07:00
requirements-dev.txt Remove codecov from requirements-dev.txt (#15487) 2023-04-12 18:48:02 -07:00
requirements-doc.txt
requirements-lintrunner.txt [Better Engineering] Bump ruff to 0.0.278 and fix new lint errors (#16789) 2023-07-21 12:53:41 -07:00
requirements-training.txt Remove protobuf pin from training requirements (#13695) 2022-11-22 12:27:18 -08:00
requirements.txt.in Add additional python requirements (#11522) 2022-05-20 16:16:18 -07:00
SECURITY.md Microsoft mandatory file (#11619) 2022-05-25 13:56:10 -07:00
setup.py Add mac and windows python packages for onnxruntime-training (#16993) 2023-08-07 20:32:55 -07:00
ThirdPartyNotices.txt Support SmoothQuant for ORT static quantization (#16288) 2023-07-26 18:56:45 -07:00
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
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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.