OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
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[CPU] Optimize quantization scheme for SPR/ATS (#7549)
* [CPU] Optimize quantization scheme for SPR/ATS

* [CPU] [LPT] plugin tests

* [GPU] [LPT] plugin tests

* [CPU] limitation was removed

* [CPU] optimization FP32 old way support

* [LPT] comment fix

* [LPT] Multiply plugin test improvement

* [LPT] Multiply support

* [LPT] GPU tests fix

* [LPT] test quick fix

* [LPT] new ppi fix

* look like spent time for tests refactoring
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.ci [MO] Azure CI, unit-test dirs and howto doc fixes (#9146) 2021-12-17 15:56:40 +03:00
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src [CPU] Optimize quantization scheme for SPR/ATS (#7549) 2021-12-20 11:19:40 +03:00
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OpenVINO™ Toolkit

Stable release Apache License Version 2.0 GitHub branch checks state Azure DevOps builds (branch) PyPI Downloads

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.