OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
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Gladilov, Gleb 18f7e4f4f0
[IE][VPU]: Improves myriad plugin API (#2816)
LoadNetwork takes network argument by constant reference.
Myriad plugin implementation applies transformations to
given network in order to get compiled model.
Transformations take network argument by non-constant
reference, so at some point of time network copy must be
acquired. ICNNNetwork is neither copyable nor movable, so
the only way to get network copy is using special utility
returning std::shared_ptr.

Myriad plugin does not expose any ownership strategy,
so prefers to take network argument by simple reference.
Plugin also requires nGraph -> CNN conversion during
LoadNetwork implementation. Conversion utilities returns
std::shared_ptr, which makes plugin to use workaround for
lifetime of converted object (to have 2 "pointers" to
network: raw pointer to input network and smart pointer to
converted network). Such workarounds make code more
error-prone, because using wrong pointer to semantically
the same object may lead to unexpected results.

To overcome these issues API has been changed in a way to
make interfaces more clear (do not expose ownership strategy
or mutability) and get rid of unnecessary workarounds.

Signed-off-by: Gladilov, Gleb <gleb.gladilov@intel.com>
2020-10-28 11:14:14 +03:00
.ci Add watchdog of OpenVino ONNX CI (#2550) 2020-10-23 14:16:43 +02:00
.github GitHub CI: Add files_size.yml (#2570) 2020-10-13 13:27:34 +03:00
cmake Openvino extra module adding - refactored (#2754) 2020-10-23 08:54:48 +03:00
docs fix path to code snippets in Custom_ONNX_Ops.md (#2764) 2020-10-28 06:20:52 +03:00
inference-engine [IE][VPU]: Improves myriad plugin API (#2816) 2020-10-28 11:14:14 +03:00
licensing added third party programs files (#2751) 2020-10-23 18:03:01 +03:00
model-optimizer ONNX Loop operation support (#2756) 2020-10-27 23:04:43 +03:00
ngraph [CPU] Generic JIT Eltwise implementation (#1464) 2020-10-28 09:16:28 +03:00
openvino Fix itt build (#2662) 2020-10-14 18:35:21 +03:00
scripts setupvars.sh: Updated setting pyenv error to warning. (#2663) 2020-10-14 18:33:17 +03:00
tests Remove memcheck_pregen_irs_tests MemCheck configs due obsolescence (#2693) 2020-10-19 09:48:38 +03:00
tools Supported threading command line options for other devices (#2725) 2020-10-21 06:40:18 +03:00
.gitattributes Doc Migration (master) (#1377) 2020-07-20 17:36:08 +03:00
.gitignore publish master branch snapshot, revision 8d31237e2c3f673cbb0f0ba110fc10f5cce1d2bb 2020-05-22 02:23:12 +03:00
.gitmodules add submodules for mkl-dnn, gflags and gtest 2020-05-21 23:00:55 +03:00
build-instruction.md Feature/azaytsev/merge to master (#2786) 2020-10-27 00:41:46 +03:00
CMakeLists.txt Removed obsolete comments from cmake (#2748) 2020-10-22 16:11:28 +03:00
CODEOWNERS Added code owners for scripts folder (#2130) 2020-09-08 17:23:27 +03:00
CONTRIBUTING_DOCS.md docs contribution guides (#1535) 2020-08-07 15:33:11 +03:00
CONTRIBUTING.md Create CONTRIBUTING.md 2020-05-19 19:04:27 +03:00
get-started-linux.md Updating broken link on getting started linux doc (#2507) 2020-10-16 19:02:41 +03:00
install_build_dependencies.sh [install_dependencies.sh] install latest cmake if current version is lower 3.13 (#2695) 2020-10-16 21:03:46 +03:00
Jenkinsfile Bump infra 2020-10-27 15:12:33 +03:00
LICENSE Publishing R3 2018-10-16 13:45:03 +03:00
README.md doc: add openvino tag link on StackOverflow (#2585) 2020-10-08 16:17:30 +03:00
SECURITY.md Fix link in SECURITY.md (#2259) 2020-09-21 21:35:24 +03:00

OpenVINO™ Toolkit - Deep Learning Deployment Toolkit repository

Stable release Apache License Version 2.0 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 two components: namely Model Optimizer and Inference Engine, as well as CPU, GPU 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.

Documentation

How to Contribute

See CONTRIBUTING for contribution to the code. See CONTRIBUTING_DOCS for contribution to the documentation. Thank you!

Support

Please report questions, issues and suggestions using:


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