Ilya Lavrenov 0bebd53b4a Inference chaining: static and dynamic cases (#7776)
* Fixed precisions conversion in new API

* Added tests

* Fixed old IR cases

* Disable FP16

* Fixed regex for CentoOS

* Refactored tests to use new API

* Temp

* Fixed tests

* Moved smart reshape related sources to ngraph

* Added tests for invalid names

* Moved reshape to tensor_names

* clang-format

* Fixed CC build

* Removed IEConv, IEDeconv from primitives pririty

* Added tests for Inference chaining

* Fixed dynamic chaining for template plugin

* Added test for 2 conflicting names for the single parameter

* Removed invalid test

* Added more tests for dynamism

* Fixed clang-format

* Fixed macosx compilation

* Some simplifications
2021-10-04 14:51:14 +03:00
2021-09-24 17:24:44 +03:00
2021-09-13 13:39:42 +03:00
2021-10-04 11:14:13 +03:00
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) 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:

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

Languages
C++ 80.5%
Python 15.5%
C 2.8%
CMake 0.9%
Cython 0.1%