Alexey Lebedev 1efb0a034f [PYTHON API] release GIL (#10810)
* AsyncInferQueue nogil update + refactoring

* nogil in compiled model

* nogil in Core

* fix refactoring

* nogil in infer_request

* add tests

* Fix code style

* update test with incrementing reference counting

* try to fix code style

* fix code style

* release gil in reshape and preprocessing

* make args optional in test

* fix code style

* add docs about GIL

* try to link doc string with docs

* Apply suggestions from code review

Co-authored-by: Jan Iwaszkiewicz <jan.iwaszkiewicz@intel.com>

* Fix docs

* docs refactoring

* Apply review comments

* Fix code style

Co-authored-by: Jan Iwaszkiewicz <jan.iwaszkiewicz@intel.com>
Co-authored-by: Anastasia Kuporosova <anastasia.kuporosova@intel.com>
2022-03-31 16:12:48 +03:00
2022-03-31 16:12:48 +03:00
2022-03-31 16:12:48 +03:00
2022-03-31 14:07:07 +03:00
2021-05-31 15:24:56 +03:00
2018-10-16 13:45:03 +03:00
2022-03-30 16:10:03 +03:00
2020-11-17 16:44:44 +03:00

OpenVINO™ Toolkit

Stable release Apache License Version 2.0 GitHub branch checks state Azure DevOps builds (branch) PyPI Downloads

This toolkit allows developers to deploy pre-trained deep learning models through a high-level OpenVINO™ Runtime C++ and Python APIs integrated with application logic.

This open source version includes several components: namely Model Optimizer, OpenVINO™ Runtime, Post-Training Optimization Tool, 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 TensorFlow, ONNX, PaddlePaddle, MXNet, Caffe, Kaldi.

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License

OpenVINO™ 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.

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Languages
C++ 80.5%
Python 15.5%
C 2.8%
CMake 0.9%
Cython 0.1%