OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
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Dawid Kożykowski b4ad7a1755
Refactor visitor tests for BinaryElementwiseArithmetic ops (#6667)
* add binary_elementwise file

* change binary_elementwise.hpp to binary_ops.hpp

* migrate mod operation test o typed template test

* add tests for remaining binary ops

* remove comment

* fix formatting to match clang-format

* add RVO-exploit string concatenating andbeautify the code

* add validation for attributes number

* add missing visit_attributes() calls

* add missing 4th param to NGRAPH_RTTI_DEFINITION calls

* fix formatting to match clang-format
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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*.

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:

Support

Please report questions, issues and suggestions using:


* Other names and brands may be claimed as the property of others.