ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
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Changming Sun a22dc65a81
Add a missing header to cuda_common.h (#15489)
### Description

The following three lines are needed before including some cutlass
header files, because cutlass uses "and"/"or" keywords. Generally it
should not be a problem without this header, but nvcc is not strictly
compliant to C++ standard.

```c++
#ifdef __cplusplus
#include <ciso646>
#endif
```

We didn't hit this problem because the above code exists in absl. We
always include absl headers first. However, ABSL recently deleted them!
https://github.com/abseil/abseil-cpp/pull/1246

The cutlass dependency was introduced in #14343 , after we had abseil.
2023-04-12 22:16:59 -07:00
.config Update tsaoptions.json: update the email alias (#13448) 2022-10-26 15:56:16 -07:00
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.pipelines WindowsAI build failing due to deprecated .NET5 SDK missing in build image (#15383) 2023-04-06 08:51:07 -07:00
.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 [TensorRT EP] support TensorRT 8.6-EA (#15299) 2023-04-12 11:34:59 -07:00
cmake Optimize SCE loss compute (#15401) 2023-04-13 13:02:12 +08:00
csharp Implement Optional Metadata support and C# test support (#15314) 2023-04-11 09:41:59 -07:00
dockerfiles Update build.py to disallow running as root user by default. (#15164) 2023-03-27 14:46:04 -07:00
docs Optimize SCE loss compute (#15401) 2023-04-13 13:02:12 +08:00
include/onnxruntime/core Implement Optional Metadata support and C# test support (#15314) 2023-04-11 09:41:59 -07:00
java [java] Allows the creation and extraction of zero length tensors (#15116) 2023-04-05 10:49:59 -07:00
js [wasm] optimize default session options parsing (#15428) 2023-04-10 11:09:09 -07:00
objectivec Add workflow to update Objective-C docs. (#15413) 2023-04-07 15:00:15 -07:00
onnxruntime Add a missing header to cuda_common.h (#15489) 2023-04-12 22:16:59 -07:00
orttraining Optimize SCE loss compute (#15401) 2023-04-13 13:02:12 +08:00
package/rpm Bump ORT version number (#14226) 2023-01-26 12:33:47 -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
tools [build/npm] dump ORT_COMMON_FROM from validation (#15475) 2023-04-12 13:48:19 -07:00
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.lintrunner.toml Run rustfmt in CI (#15217) 2023-03-27 08:12:59 -07:00
build.amd64.1411.bat
build.bat
build.sh
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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
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packages.config Download protoc.exe from nuget when cross-compiling (#15395) 2023-04-06 17:06:59 -07:00
pyproject.toml Upgrade remainding python to 3.11 removing 3.7 (#15321) 2023-04-05 21:43:51 -07:00
README.md [Readme] Update table for build pipelines (#14618) 2023-02-08 09:44:20 -08:00
requirements-dev.txt Remove codecov from requirements-dev.txt (#15487) 2023-04-12 18:48:02 -07:00
requirements-doc.txt
requirements-training.txt Remove protobuf pin from training requirements (#13695) 2022-11-22 12:27:18 -08:00
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SECURITY.md
setup.py Adopt linrtunner as the linting tool - take 2 (#15085) 2023-03-24 15:29:03 -07:00
ThirdPartyNotices.txt Revert mimalloc from v2.0.9 to v2.0.3 (#14603) 2023-02-07 09:58:25 -08:00
VERSION_NUMBER Bump ORT version number (#14226) 2023-01-26 12:33:47 -08:00

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.