ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
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Changming Sun 67bc9438d7
Update training packaging pipeline's docker files (#20853)
### Description
Similar to #20786 . The last PR was able to update all pipelines and all
docker files. This is a follow-up to that PR.

### Motivation and Context
1. To extract the common part as a reusable build infra among different
ONNX Runtime projects.
2. Avoid hitting docker hub's limit: 429 Too Many Requests - Server
message: toomanyrequests: You have reached your pull rate limit. You may
increase the limit by authenticating and upgrading:
https://www.docker.com/increase-rate-limit
2024-05-30 23:48:42 -07:00
.config
.devcontainer
.gdn
.github [CPU EP] Int4 support for QuantizeLinear, DequantizeLinear, and Transpose (#20362) 2024-05-30 18:56:24 -07:00
.pipelines Update DML to 1.14.1 (#20380) 2024-04-18 22:43:41 -07:00
.vscode disable gemm f16 on CPU (#19744) 2024-03-01 13:44:29 -08:00
cgmanifests Update RE2 to the latest (#20775) 2024-05-23 14:30:15 -07:00
cmake Update Aten pipeline's docker file to use UBI8 (#20856) 2024-05-30 07:38:15 -07:00
csharp Remove ref struct return usage (#20132) 2024-05-16 09:46:19 -07:00
dockerfiles OpenVINO EP Rel 1.18 Changes (#20337) 2024-04-19 00:31:38 -07:00
docs [CPU EP] Int4 support for QuantizeLinear, DequantizeLinear, and Transpose (#20362) 2024-05-30 18:56:24 -07:00
include/onnxruntime/core [CPU EP] Int4 support for QuantizeLinear, DequantizeLinear, and Transpose (#20362) 2024-05-30 18:56:24 -07:00
java adding publishing stage to publish java CUDA 12 pkg to ado (#20834) 2024-05-29 16:24:23 -07:00
js [js/webgpu] Fix mha name (#20860) 2024-05-30 00:01:06 -07:00
objectivec Fix Objective-C static analysis warnings. (#20417) 2024-04-24 11:48:29 -07:00
onnxruntime Fix bench_sqnbitgemm.cpp benchmark argument name list. (#20858) 2024-05-30 18:59:54 -07:00
orttraining [Training] Add bf16 support to GatherElementsGrad. (#20796) 2024-05-24 15:55:14 -07:00
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 Update training packaging pipeline's docker files (#20853) 2024-05-30 23:48:42 -07:00
winml [DML EP] Add GroupQueryAttention (#20327) 2024-04-19 10:25:29 -07:00
.clang-format
.clang-tidy
.dockerignore
.gitattributes
.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 Support >2GB of Tensor data in training checkpoint (#20077) 2024-04-22 15:17:43 -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 ORT ETW dynamic logging that improves ORT diagnosability & performance (#18882) 2024-01-11 12:43:27 -08:00
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
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
requirements.txt.in
SECURITY.md
setup.py Update setup.py: update TRT version (#20557) 2024-05-03 22:39:20 -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
Windows Build Status
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Linux Build Status
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Mac Build Status
Android Build Status
iOS Build Status
Web Build Status
Other Build Status

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.