ff1046c0e1
* Disable v10 serealizer (#3184)
* Disable v10 serealizer
* Fixed comments
* Backport of PR #3092 - TopK sorting fix (#3195)
* [IE] - Interpolate ONNX workaround (#3203)
Co-authored-by: DariaMityagina <daria.mityagina@intel.com>
* Fix NMS1/3/4 to Legacy conversion (#3210)
* Fix NMS1/3/4 to Legacy conversion
* Added functoinal tests
* [LPT] Transpose, MatMul: Klocwork fixes (#3192)
* Update install_openvino_dependencies.sh (#3196)
* [ MO TF ] TF FakeQuantize normalization fix (#3180)
* Specify sliced input of Loop op
* Enable back rpecalcu;ated ref falues for TrivialLoop tests
Signed-off-by: Alexander Peskov <alexander.peskov@intel.com>
* [NGRAPH] Add sliced input to Loop op
Signed-off-by: Alexander Peskov <alexander.peskov@intel.com>
* Add loop test with input slicing
Signed-off-by: Alexander Peskov <alexander.peskov@intel.com>
* One more test on loop
Signed-off-by: Alexander Peskov <alexander.peskov@intel.com>
* [ nG: TI ] Fix for reshaping TensorIterator
* Trigger CI
* Fix dyn auto slicing tests
* ngraph codestyle
* misprint
* style
* style
* Fix reshaping Loop
* ngraph codestyle
* delete unnecessary comments
* Revert "Disable v10 serealizer (#3184)"
This reverts commit 5abbe2fec5.
Co-authored-by: Ilya Churaev <ilya.churaev@intel.com>
Co-authored-by: Tomasz Jankowski <tomasz1.jankowski@intel.com>
Co-authored-by: Andrey Sokolov <andrey.sokolov@intel.com>
Co-authored-by: DariaMityagina <daria.mityagina@intel.com>
Co-authored-by: Gleb Kazantaev <gleb.kazantaev@intel.com>
Co-authored-by: Vladislav Golubev <vladislav.golubev@intel.com>
Co-authored-by: Dmitrii Denisov <dmitrii.denisov@intel.com>
Co-authored-by: Evgenya Stepyreva <evgenya.stepyreva@intel.com>
Co-authored-by: Alexander Peskov <alexander.peskov@intel.com>
OpenVINO™ Toolkit - Deep Learning Deployment Toolkit repository
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
- Additional OpenVINO modules: https://github.com/openvinotoolkit/openvino_contrib
- HomePage
- OpenVINO™ Release Notes
Support
Please report questions, issues and suggestions using:
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openvinotag on StackOverflow* - GitHub* Issues
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