OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
aicomputer-visiondeep-learningdeploy-aidiffusion-modelsgenerative-aigood-first-issueinferencellm-inferencenatural-language-processingnlpopenvinooptimize-aiperformance-boostrecommendation-systemspeech-recognitionstable-diffusiontransformersyolo
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* Squash commit: implement Conversion extensions * Refactor PaddlePaddle FrontEnd * Codestyle * FrontEnd,InputModel,Place base classes -> abstract, renamed model file * Fix unit tests * fix unit tests * ngraph:: to ov:: * Rename frontends dir to frontend * fix merge conflicts * Fix ConversionExtension * get rid of NamedInputs/Outputs in TF FE * Rename paddlepaddle to paddle; pdpd to paddle * add missing file * codestyle * Remove local change * paddlepaddle -> paddle for azure configs and .md files * fix package name, fix config files * Fix win build * Revert Broadcast/AutoBroadcast changes * codestyle * fix FronEnd class * fix ngraph_cpp_api.config * fix incorrect merge, codestyle * fix conversion extension * conversion extension * codestyle * merge master * fix build * refactoring; revert broadcast/autobroadcast changes * codestyle * fix MacOS config * resolve merge conflicts * refactor includes * register ConversionExtension in FrontEnds * move get_op_type to base NodeContex class * set op_translator map in ctor of Paddle FE; fix unit tests * update unit tests; codestyle * codestyle * preliminary version of conversion extension in pybind * conversion extension * get_attribute_as_any method for NodeContext * move get_attribute methods to NodeContext base class, rename get_ng_input to get_input * add missed file * Implement ov::Any getter in ONNX NodeContext * fix py bindings * Add update ConversionExtension unit tests, add SO unit tests, fix TF FE * fix segfault on destructor * fix NodeContext interface, fix unit tests * set different names for ConversionExtensions in unit tests * fix PaddleFuzzy tests * fix Paddle Fuzzy tests * revert changes in generate_slice.py * fix codestyle * fix pybindings * revert local changes in generate_slice.py * delete duplicate exceptions.hpp * Refactoring: fix names according to convention * pybinding for NodeContext, FrontEnd, ConversionExtension; fix unit tests; implement new unit tests * Refactoring * fix the case when a new converter rewrites existed one; delete unnecessary NodeContext from pybindings; use CreatorFunctons from the base class in ConversionExtension; update unit tests * Revert local change * PythonAPI: fix get_attribute method; fix get_input method; implement support of dtype and default attributes * Fix py unit tests: add support for vector<ov::element::Type> as attribute * resolve review comments * fix unit tests * move extension_holder to openvino/frontend/extension folder * fix build on mac os * temporary disable cast from vector<bool> to investigate issue on mac os * Resolve review comments * Resolve review comments * Use dev API for .so extension * Link frontends to pyopenvino as separate targets * Temporary enable tf fe installation * ignore PEP8 E402 for init files, set correct directory for py modules * revert local changes * Fix deadlock in pybind GIL; fix Win build; fix PEP8 * fix PEP8 * Add a return type annotation * fix builds; fix ON/OFF switcher for ENABLE_OV_xxx_FRONTEND cmake options * Fix the issue with ifdefs on WinOS; fix the issue related to pybindings and static c++ object * fix python unit tests * fix static build on WinOS * Retrigger CI builds * Fix static build on Windows * fix static build on Windows again * Retrigger CI * delete unused includes; add a comment about issue on MacOS * fix missprint * resolve review comments * fix missprint * resolve review remarks * Resolve review comments * win win wheels build * resolve review comments |
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OpenVINO™ Toolkit
This toolkit allows developers to deploy pre-trained deep learning models through a high-level C++ Inference Engine API integrated with application logic.
This open source version includes several components: namely Model Optimizer, nGraph and Inference Engine, as well as CPU, GPU, MYRIAD, multi device and heterogeneous plugins to accelerate deep learning inferencing on Intel® CPUs and Intel® Processor Graphics. It supports pre-trained models from the Open Model Zoo, along with 100+ open source and public models in popular formats such as Caffe*, TensorFlow*, MXNet* and ONNX*.
Repository components:
License
Deep Learning Deployment Toolkit is licensed under Apache License Version 2.0. By contributing to the project, you agree to the license and copyright terms therein and release your contribution under these terms.
Resources:
- Docs: https://docs.openvinotoolkit.org/
- Wiki: https://github.com/openvinotoolkit/openvino/wiki
- Issue tracking: https://github.com/openvinotoolkit/openvino/issues
- Storage: https://storage.openvinotoolkit.org/
- Additional OpenVINO™ modules: https://github.com/openvinotoolkit/openvino_contrib
- Intel® Distribution of OpenVINO™ toolkit Product Page
- Intel® Distribution of OpenVINO™ toolkit Release Notes
Support
Please report questions, issues and suggestions using:
- The
openvinotag on StackOverflow* - GitHub* Issues
- Forum
* Other names and brands may be claimed as the property of others.