ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
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Ye Wang d9c744ed9a
Fix a bug in t5 beamsearch with half precision (#14436)
the CreateEncoderInputs functor was passed to the ctor as nullptr when
type is MLFloat16.

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### Motivation and Context
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2023-01-26 11:14:22 -08:00
.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
.github Delete add-issues-to-project (#14147) 2023-01-11 14:33:37 -08:00
.pipelines [DML EP] Upgrade DML to 1.10.1 (#14433) 2023-01-25 21:07:10 -08:00
.vscode cpplint & Eager mode: refactor and add comments to empty_* functions, general lint cleanup in ort_aten (#12238) 2022-07-20 11:47:57 -04:00
cgmanifests Upgrade CUTLASS to v2.11 and add sequence length threshold for cutlass FMHA (#14401) 2023-01-25 09:43:48 -08:00
cmake [DML EP] Upgrade DML to 1.10.1 (#14433) 2023-01-25 21:07:10 -08:00
csharp Remove exclusions for ONNX model tests that now pass. (#14337) 2023-01-24 08:04:27 +10:00
dockerfiles Openvino ep 2022.3 v4.3 (#14210) 2023-01-11 16:31:26 -08:00
docs cpu support of LpPool(18) (#14205) 2023-01-25 23:14:56 -08:00
include/onnxruntime/core Ort openvino 4.3 cli (#14341) 2023-01-23 14:17:52 -08:00
java Add Java and Objective-C bindings for RegisterCustomOpsUsingFunction. (#14256) 2023-01-13 09:04:26 -08:00
js [js] upgrade packages in js/web/test/e2e (#14334) 2023-01-25 18:03:48 -08:00
objectivec [objc] Fix parameter name in documentation. (#14330) 2023-01-18 16:54:59 -08:00
onnxruntime Fix a bug in t5 beamsearch with half precision (#14436) 2023-01-26 11:14:22 -08:00
orttraining Extend ort_backend.py for another ep (#14349) 2023-01-20 07:30:00 -08:00
package/rpm Bumping up version number to 1.14.0 on main branch (#13401) 2022-10-21 19:16:44 -04:00
samples Format all python files under onnxruntime with black and isort (#11324) 2022-04-26 09:35:16 -07:00
test Multi-stream execution support (#13495) 2022-12-15 07:39:29 -08:00
tools [DML EP] Upgrade DML to 1.10.1 (#14433) 2023-01-25 21:07:10 -08:00
winml Enabling thread pool to be numa-aware (#13778) 2022-12-12 10:33:55 -08:00
.clang-format
.clang-tidy Create clang-tidy CI (#12653) 2022-09-30 08:05:38 -07:00
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.flake8 Remove miscellaneous nuphar configs (#13070) 2022-09-26 13:41:28 -07:00
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.gitmodules Remove unused git submodules (#13830) 2022-12-07 21:59:16 -08:00
build.amd64.1411.bat
build.bat
build.sh
CITATION.cff Fix CITATION.cff and add automatic validation of your citation metadata (#10478) 2022-04-13 10:03:52 -07:00
CODEOWNERS Add cgmanifest file in codeowner list (#13042) 2022-09-22 18:58:01 -07:00
CONTRIBUTING.md Fix broken link (#14368) 2023-01-20 15:55:03 -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 Update nuget icon (#10672) 2022-03-01 09:11:03 -08:00
packages.config [DML EP] Upgrade DML to 1.10.1 (#14433) 2023-01-25 21:07:10 -08:00
pyproject.toml Update pylint config to include valid short names (#13631) 2022-11-14 10:00:25 -08:00
README.md Update resource section in readme (#13724) 2022-11-28 09:42:31 -08:00
requirements-dev.txt Introduce parameterized as a dev dependency (#11364) 2022-04-26 17:24:39 -07:00
requirements-doc.txt
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 Openvino ep 2022.3 v4.3 (#14210) 2023-01-11 16:31:26 -08:00
ThirdPartyNotices.txt Add memory efficient attention from CUTLASS (#14343) 2023-01-20 12:33:01 -08:00
VERSION_NUMBER Bumping up version number to 1.14.0 on main branch (#13401) 2022-10-21 19:16:44 -04:00

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

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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.