ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
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Edward Chen baf8c39a8d
Add Python checks pipeline (#7032)
This change adds a new pipeline for checking Python code. Currently this pipeline only runs flake8.
flake8 is also run as part of the CMake project builds, but we can switch over completely to the new pipeline later.
The .flake8 config file was also updated to make it easier to run standalone (flake8 --config ./.flake8) and some Python formatting issues were addressed in files that were not previously scanned.
2021-08-09 10:37:05 -07:00
.gdn Update compliance tasks in python packaging pipeline and fix some compile warnings (#8471) 2021-07-30 17:16:37 -07:00
.github Update issue template to ask users to check known issues to avoid repetition. (#8288) 2021-07-02 15:36:14 -07:00
cgmanifests Add Python checks pipeline (#7032) 2021-08-09 10:37:05 -07:00
cmake Integrate eager mode source code into onnxruntime repo (#8584) 2021-08-06 08:30:27 -07:00
csharp Add Python checks pipeline (#7032) 2021-08-09 10:37:05 -07:00
dockerfiles [OpenVINO-EP 2021.4] Add/update Dockerfiles w.r.t OpenVINO 2021.4 Version (#8491) 2021-08-02 15:13:46 -07:00
docs doc: add ort-web related instructions to update onnx doc (#8500) 2021-08-06 15:09:11 -07:00
include/onnxruntime/core Fix bug in CPU force fallback logic (#8597) 2021-08-05 21:36:28 -07:00
java Add UINT8 datatype support to Java (#8401) 2021-07-22 17:11:49 -07:00
js [js/node] fix js node install (#8650) 2021-08-06 23:36:53 -07:00
objectivec [Objective-C API] Fix ORTIsCoreMLExecutionProviderAvailable link error when used from Swift. (#8350) 2021-07-14 18:38:58 -07:00
onnxruntime [js] resolve CodeQL warnings for force strict mode (#8645) 2021-08-06 19:35:43 -07:00
orttraining constrain inputs for min/max grad UT (#8632) 2021-08-07 18:29:06 +08:00
package/rpm bumping onnxruntime version to 1.8.1 (#8429) 2021-07-19 16:48:56 -07:00
samples Add Python checks pipeline (#7032) 2021-08-09 10:37:05 -07:00
server fix boost download url (#7843) 2021-05-26 16:08:57 -07:00
tools Add Python checks pipeline (#7032) 2021-08-09 10:37:05 -07:00
winml remove unused functions to avoid warnings 2021-07-28 18:03:00 -07:00
.clang-format
.clang-tidy
.dockerignore
.flake8 Add Python checks pipeline (#7032) 2021-08-09 10:37:05 -07:00
.gitattributes
.gitignore Integrate eager mode source code into onnxruntime repo (#8584) 2021-08-06 08:30:27 -07:00
.gitmodules Upgrade TensorRT to v8.0.1 (#8512) 2021-08-02 11:20:31 -07:00
build.amd64.1411.bat
build.bat
build.sh
CODEOWNERS Update CODEOWNERS with mobile team ownership of expected kernel def hash data files. (#8454) 2021-07-22 11:19:06 -07:00
CONTRIBUTING.md Add README for docs (#6626) 2021-03-12 15:14:40 -08:00
LICENSE Remove year from license (#6658) 2021-02-12 00:25:56 -08:00
NuGet.config Delete nuget extra configs (#6477) 2021-01-27 20:25:45 -08:00
ort.wprp
packages.config Update DirectML version to 1.5.1 and enable ARM/ARM64 builds with DML (#7511) 2021-04-30 00:49:30 -07:00
README.md Add link to sample repos (#8417) 2021-07-21 16:18:59 -07:00
requirements-dev.txt Add post-install command to build PyTorch CPP extensions from within onnxruntime package (#8027) 2021-06-28 18:11:58 -07:00
requirements-doc.txt Add auto doc gen for ORTModule API during CI build (#7046) 2021-03-22 10:20:33 -07:00
requirements-training.txt Add post-install command to build PyTorch CPP extensions from within onnxruntime package (#8027) 2021-06-28 18:11:58 -07:00
requirements.txt.in Chang how numpy version is handled. (#8130) 2021-06-23 14:08:37 -07:00
setup.py Add Python checks pipeline (#7032) 2021-08-09 10:37:05 -07:00
ThirdPartyNotices.txt Adding pytorch cpuinfo as dependency (#8178) 2021-07-12 14:21:12 -07:00
VERSION_NUMBER bumping onnxruntime version to 1.8.1 (#8429) 2021-07-19 16:48:56 -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

General Information: onnxruntime.ai

Usage documention and tutorials: onnxruntime.ai/docs

Companion sample repositories:

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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.