Dawid Kożykowski 3081fac758 Unify SLTs classes of Convert and ConvertLike operations (#7129)
* update comparisiofiles to use const ref param

* introduce conversion layer test definitions

* adapt old tests to the new format

* remove old duplicated conversion tests

* fix "convertion" typo to "conversion"

* fix style issues and abandon unnecessary changes

* fix include order

* update remaining conversion tests to use introduced class

* fix gpu class test naming

* bring back convert.hpp and convert_like.hpp files

* bring back convert.hppcppd convert_like.cpp files

* bring back single_layer_tests/convert.hpp file

* add missing copyright info

* fix issue with braces initiator for conversion types

* add missing convert_like tests

* add deprecated code macros

* update deprecated code macro message

* add missing space in deprecated code macro message

* update skip ConvertLike tests ticket

* update deprecated code to  use IE macros

* update remaining ngraph_deprecated macros to use IE macros
2021-09-01 14:19:38 +03:00
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2021-05-31 15:24:56 +03:00
2018-10-16 13:45:03 +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)

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*.

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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.

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