Andrey Kashchikhin
24b414c168
* add onnx models test job * rm sudo * add missing update * add missing git-lfs * add missing package * correct var * correct command * try with pytest * provide path to models * use mounted path * add msft models * use symlinks * correct name for model * use -h * create and use directory for models * use share as source for models * fix test names, use fresh onnx repo * return names * fix test names * change folder structure for onnx model downloading * skip tests; clean up logs; adapt azure counterpart * make skip names lowercase * increase parallel * add missing git-lfs * fix dir * install git-lfs properly * use sudo * use 12 parallels; rm -f * use skip * rm unnecessary requirements * rm pytorch from installing * disable test
OpenVINO™ Core Components
This section provides references and information about OpenVINO core components.
bindings/ // OpenVINO bindings
cmake/ // Common cmake scripts
common/ // Common components
core/ // OpenVINO core component provides model representation, operations and other core functionality
frontends/ // OpenVINO frontends
inference/ // Provides API for model inference
plugins/ // OpenVINO plugins
tests/ // A backed of tests binaries for core and plugins
OpenVINO Runtime library
OpenVINO Runtime is a common OpenVINO library which provides functionality for Neural Network inference. The library includes next parts:
flowchart LR
subgraph openvino [openvino library]
core
inference
transformations[Common transformations]
lp_transformations[LP transformations]
frontend_common
style frontend_common fill:#7f9dc0,stroke:#333,stroke-width:4px
style transformations fill:#3d85c6,stroke:#333,stroke-width:4px
style lp_transformations fill:#0b5394,stroke:#333,stroke-width:4px
style core fill:#679f58,stroke:#333,stroke-width:4px
style inference fill:#d7a203,stroke:#333,stroke-width:4px
end
- core is responsible for model representation, contains a set of supported OpenVINO operations and base API for model modification.
- inference provides the API for model inference on different accelerators.
- Transformations:
- common transformations - a set of common transformations which are used for model optimization
- low precision transformations - a set of transformations which are needed to optimize quantized models
- frontend_common provides frontend common API which allows to support frontends for different frameworks.
OpenVINO Frontends
OpenVINO Frontends allow to convert model from framework to OpenVINO representation.
Go to the Frontends page to get more information.
OpenVINO Plugins
OpenVINO Plugins provide support for hardware devices.
To get more information about supported OpenVINO Plugins, go to the Plugins page.
OpenVINO Bindings
OpenVINO provides bindings for different languages. To get the full list of supported languages, go to the bindings page.