OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
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Piotr Szmelczynski 42bbe979b1
type_prop template for arithmetic ops (#4941)
* create type_prop template for arithmetic ops

* make arithemtic_ops a header file

* remove power, multiply, divide, subtract and minimum from binary_elementwise

* create type_prop tests for divide

* create type_prop tests for multiply

* create type_prop tests for subtract

* update minimum type_prop tests

* update power type_prop tests

* fix style

* remove arithmetic_ops from CMakeList

* fix test
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inference-engine cmake improvements: coverage and SELECTIVE_BUILD beautifications (#4937) 2021-03-26 06:40:54 +03:00
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ngraph type_prop template for arithmetic ops (#4941) 2021-03-26 06:42:41 +03:00
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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

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