ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
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zhijiang 269d9b094f
Zhijxu/fix softmax cudnn bf16 (#21045)
if seq >2048, ort will fallback to cudnn version, while when dtype is
bf16, ort will throw exception, this PR trying to fix it.
2024-06-24 16:07:39 +08:00
.config
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.github Fix a perm issue in Windows Static Analysis pipeline (#21100) 2024-06-19 14:44:39 -07:00
.pipelines Fix onebranch exception in code signing (#21088) 2024-06-19 12:07:17 +08:00
.vscode disable gemm f16 on CPU (#19744) 2024-03-01 13:44:29 -08:00
cgmanifests [ROCm] Update ck to use ck_tile (#21030) 2024-06-19 14:06:10 +08:00
cmake Revert "[MIGraphX EP] enable compilation and execution on Windows (21084)" (#21132) 2024-06-21 01:01:07 -07:00
csharp Update to the net8 MAUI targets. Remove Xamarin. (#21062) 2024-06-19 16:20:58 +10:00
dockerfiles Update Dockerfile.cuda (#21042) 2024-06-13 23:50:03 -07:00
docs Rename a mispelled filename in the documentation (#21066) 2024-06-17 18:18:41 +02:00
include/onnxruntime/core [MIGraphX EP] Add migraphx ep save load compiles (#20643) 2024-06-17 11:24:31 +08:00
java Remove deprecated "mobile" packages (#20941) 2024-06-07 16:20:32 -05:00
js [WebNN EP] Update Prelu restriction for CPU backend (#20878) 2024-06-20 11:04:01 -07:00
objectivec Fix Objective-C static analysis warnings. (#20417) 2024-04-24 11:48:29 -07:00
onnxruntime Zhijxu/fix softmax cudnn bf16 (#21045) 2024-06-24 16:07:39 +08:00
orttraining Zhijxu/fix softmax cudnn bf16 (#21045) 2024-06-24 16:07:39 +08:00
rust Fix rust compile issues and add GH action to run build validations and tests (#18346) 2023-11-09 04:26:02 -08:00
samples Removed all the deprecated python training code and related tests and utils (#18333) 2023-11-17 18:19:21 -08:00
tools Add UsePython Task in Nuget Publish workflow (#21144) 2024-06-24 13:36:13 +08:00
winml [DML EP] Add GroupQueryAttention (#20327) 2024-04-19 10:25:29 -07:00
.clang-format
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.gitignore Build onnxruntime.dll as arm64x (#18633) 2023-12-06 16:49:00 -08:00
.gitmodules [js/web] optimize module export and deployment (#20165) 2024-05-20 09:51:16 -07:00
.lintrunner.toml Adding a sm80 q4 gemm kernel for small tiles (#20545) 2024-06-12 16:02:26 -07:00
build.bat
build.sh
build_arm64x.bat remove unnecessary environment variable (#19166) 2024-01-16 16:24:37 -08:00
CITATION.cff Fix citation author name issue (#19597) 2024-02-22 17:03:56 -08:00
CODEOWNERS
CONTRIBUTING.md
lgtm.yml
LICENSE
NuGet.config
ort.wprp Fully dynamic ETW controlled logging for ORT and QNN logs (#20537) 2024-06-06 21:11:14 -07:00
ORT_icon_for_light_bg.png
packages.config Update DML to 1.14.1 (#20380) 2024-04-18 22:43:41 -07:00
pyproject.toml [CUDA] Add SparseAttention operator for Phi-3-small (#20216) 2024-04-30 09:06:29 -07:00
README.md Update README.md (#18963) 2024-01-03 17:26:25 -08:00
requirements-dev.txt ONNX 1.15 integration (#17125) 2023-09-26 14:44:48 -07:00
requirements-doc.txt
requirements-lintrunner.txt Bump ruff to 0.3.2 and black to 24 (#19878) 2024-03-13 10:00:32 -07:00
requirements-training.txt ONNX 1.15 integration (#17125) 2023-09-26 14:44:48 -07:00
requirements.txt.in
SECURITY.md
setup.py Revert "[MIGraphX EP] enable compilation and execution on Windows (21084)" (#21132) 2024-06-21 01:01:07 -07:00
ThirdPartyNotices.txt Fix HalideIR title in third party notices reference (#20190) 2024-04-05 11:12:43 -07:00
VERSION_NUMBER Bump up version in main from 1.18.0 to 1.19.0 (#20489) 2024-04-29 20:21:41 -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.