ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
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Ashwini Khade f2e19a8ccf
Updates to training pipelines to reduce CI time (#18116)
### Description
Motivation for this PR is reducing CI test time by removing unnecessary
tests from the pipelines.

Following changes are for reducing test time in pipelines:

- Skip CPU model tests in GPU builds. Training CIs run these tests as a
sanity check. There is no direct training code being tested in these
pipelines, furthermore, CPU tests are being run in CPU pipelines so no
need to run them again in GPU builds and block the GPU VM. This change
reduces testing time by 20-25 mins in all training GPU pipelines.

- Delete debug package building pipeline for linux training packages.
This was required by compiler team at some point but there have been 0
downloads of these packages.



### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
2023-10-26 14:58:57 -07:00
.config Update tsaoptions.json: update the email alias (#13448) 2022-10-26 15:56:16 -07:00
.devcontainer
.gdn Update win-ci-pipeline.yml: enable xnnpack tests (#16244) 2023-06-14 19:12:42 -07:00
.github Bump actions/checkout from 3 to 4 (#17487) 2023-09-13 09:22:21 -07:00
.pipelines Bump DirectML version from 1.12.0 to 1.12.1 (#17225) 2023-08-20 09:55:38 -07:00
.vscode Close the JSON object in settings.json (#17583) 2023-09-26 09:51:13 -07:00
cgmanifests [TensorRT EP] Use latest onnx-tensorrt parser (#18067) 2023-10-26 13:55:12 -07:00
cmake [TensorRT EP] Use latest onnx-tensorrt parser (#18067) 2023-10-26 13:55:12 -07:00
csharp Fix missing attribute on C# DOrtGetResizedStringTensorElementBuffer delegate (#17901) 2023-10-17 17:48:36 +10:00
dockerfiles Update dockerfiles/Dockerfile.source to avoid installing onnx (#17975) 2023-10-20 09:24:21 -07:00
docs Add MatMul FP4 and NF4 Support (#18066) 2023-10-25 15:34:58 -07:00
include/onnxruntime/core [DML EP] Add dynamic graph compilation (#17876) 2023-10-25 19:56:16 -07:00
java [java] Make the backing byte buffer in an OrtValue accessible (#16578) 2023-10-17 10:03:49 -07:00
js [js/web/training] Add CreateTrainingSession (#17891) 2023-10-26 09:22:10 -07:00
objectivec Objective-C Add Support to Create and Query String ORTValues (#16764) 2023-07-20 17:39:29 -07:00
onnxruntime Updates to training pipelines to reduce CI time (#18116) 2023-10-26 14:58:57 -07:00
orttraining FP16 optimizer automatically detect DeepSpeed compatibility (#18084) 2023-10-25 15:11:02 +08:00
rust rust bindings: Do not unnecessarily re-run build.rs (#17018) 2023-09-05 19:42:06 -07:00
samples [Linter] Bump ruff and remove pylint (#17797) 2023-10-05 21:07:33 -07:00
tools Updates to training pipelines to reduce CI time (#18116) 2023-10-26 14:58:57 -07:00
winml Enable onnx_test_runner to run the whole models dir in CI machine (#17863) 2023-10-12 12:01:02 +08:00
.clang-format Prevent GSL_SUPPRESS arguments from being modified by clang-format (#17242) 2023-08-22 18:26:53 -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 Remove onnxruntime extensions from list of gitmodules (#17615) 2023-09-19 17:12:14 -07:00
.lintrunner.toml FP16 optimizer automatically detect DeepSpeed compatibility (#18084) 2023-10-25 15:11:02 +08:00
build.bat try to find patch.exe in git default installation folder (#17106) 2023-08-10 21:48:13 -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
packages.config Bump DirectML version from 1.12.0 to 1.12.1 (#17225) 2023-08-20 09:55:38 -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 ONNX 1.15 integration (#17125) 2023-09-26 14:44:48 -07:00
requirements-doc.txt
requirements-lintrunner.txt [Linter] Bump ruff and remove pylint (#17797) 2023-10-05 21:07:33 -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 Merge Cuda docker files into a single one (#18020) 2023-10-24 15:17:36 -07:00
ThirdPartyNotices.txt Flash Attention v2 MHA (#17227) 2023-08-31 13:52:21 -07:00
VERSION_NUMBER Bump Up Version to 1.17.0 (#17587) 2023-09-20 11:02:58 +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

Builtin Pipeline Status

System Inference Training
Windows Build Status
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Linux Build Status
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Mac Build Status
Android Build Status
iOS 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.