Anastasia Popova 623117fe24 Serialization of old API map in nGraph. (#7840)
* Added serialization of old API map in ngraph.

* Changed order type to int64_t.

* Fixed uint64_t error, added comments.

* Apply suggestions from code review

Co-authored-by: Gleb Kazantaev <gleb.nnstu@gmail.com>

* Added tests with undefined type and empty order.

* Added set, get and has methods.

* Fix in tests.

* Apply suggestions from code review

Co-authored-by: Ilya Churaev <ilyachur@gmail.com>

* Made inline methods, changed to shared_ptr.

* Small fix.

* Moved methods to header file.

* Small fix.

Co-authored-by: Gleb Kazantaev <gleb.nnstu@gmail.com>
Co-authored-by: Ilya Churaev <ilyachur@gmail.com>
2021-10-06 23:15:45 +03:00
2021-09-13 13:39:42 +03:00
2021-10-06 18:16:58 +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:

Support

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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%