636736825c
* OpenVINO Hybrid CPUs support * Remove custom::task_arena abstraction layout * Get back to the custom::task_arena interface * Add windows.h inclusion * Fix typo in macro name * Separate TBB and TBBbind packages * Fix compile-time conditions * Fix preprocessors conditions * Fix typo * Fix linking * make linking private * Fix typo * Fix target_compile_definitions syntax * Implement CMake install logic, update sha hash for the tbbbind_2_4 package * Add tbbbind_2_4 required paths to setup_vars * Update CI paths * Include ie_parallel.hpp to ie_system_conf.cpp * Try to update dependencies scripts * Try to fix dependencies.bat * Modify dependencies script * Use static tbbbind_2_4 library * Remove redundant paths from CI * Update tbbbind package version * Make custom::task_arena inherited from tbb::task_arena * Incapsulate all TBB versions related logic inside the custom namespace * Move custom layer header to internal scope + minor improvements * Introduce new ThreadBindingType + fix compilation * Fix compilation * Use public tbbbind_2_4 package * Apply review comments * Fix compilation without tbbbind_2_4 * Fix compilation with different TBB versions Co-authored-by: Kochin, Ivan <ivan.kochin@intel.com> |
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| inference-engine | ||
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| model-optimizer | ||
| ngraph | ||
| openvino | ||
| scripts | ||
| tests | ||
| thirdparty | ||
| tools | ||
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| .gitignore | ||
| .gitmodules | ||
| CMakeLists.txt | ||
| CODEOWNERS | ||
| install_build_dependencies.sh | ||
| Jenkinsfile | ||
| LICENSE | ||
| README.md | ||
| SECURITY.md | ||
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.