River Li d792545365 [PYTHON] Add python APIs for loadNetwork and compile_network without device name (#9536)
* [PYTHON] Add python APIs for loadNetwork and compile_networt without device name

   CVS: https://jira.devtools.intel.com/browse/CVS-75249

Change-Id: Ia28e35f4ee66fc8fc5997b5bafe1b159670f9a21
Signed-off-by: River,Li <river.li@intel.com>

* Fix clang issue

Change-Id: I9988b16863af0e3883e99369f124cd05761d3210

* Fixed positional arguments issue

Change-Id: I6c3aa98bb693a619fa54fd6e96cf5eb89cdb9369

* Fixed 2 blank lines issue

Change-Id: I7f2afd7ebb80867a69d0c3ac9a6d4a38d95edb12

* Set AUTO as default device if no device name is set

Change-Id: Ic8646b12af0a2ab2fec6a07f5a12d460dcf781d7

* Resolve comments from code reviewer

Change-Id: Ia47faeb48937096e41e22ac59fbd88ec82cc6733
2022-01-19 16:09:15 +03:00
2022-01-19 11:15:40 +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*.

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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.

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