openvino/docs/IE_PLUGIN_DG/Intro.md

Overview of OpenVINO Plugin Library

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.. toctree:: :maxdepth: 1 :caption: Converting and Preparing Models :hidden:

Implement Plugin Functionality <openvino_docs_ov_plugin_dg_plugin> Implement Compiled Model Functionality <openvino_docs_ov_plugin_dg_compiled_model> Implement Synchronous Inference Request <openvino_docs_ov_plugin_dg_infer_request> Implement Asynchronous Inference Request <openvino_docs_ov_plugin_dg_async_infer_request> Provide Plugin Specific Properties <openvino_docs_ov_plugin_dg_properties> Implement Remote Context <openvino_docs_ov_plugin_dg_remote_context> Implement Remote Tensor <openvino_docs_ov_plugin_dg_remote_tensor> openvino_docs_ov_plugin_dg_plugin_build openvino_docs_ov_plugin_dg_plugin_testing openvino_docs_ie_plugin_detailed_guides openvino_docs_ie_plugin_api_references

The plugin architecture of OpenVINO allows to develop and plug independent inference solutions dedicated to different devices. Physically, a plugin is represented as a dynamic library exporting the single CreatePluginEngine function that allows to create a new plugin instance.

OpenVINO Plugin Library #######################

OpenVINO plugin dynamic library consists of several main components:

1. :doc:Plugin class <openvino_docs_ov_plugin_dg_plugin>:

   • Provides information about devices of a specific type.
   • Can create an :doc:compiled model <openvino_docs_ov_plugin_dg_compiled_model> instance which represents a Neural Network backend specific graph structure for a particular device in opposite to the ov::Model which is backend-independent.
   • Can import an already compiled graph structure from an input stream to a :doc:compiled model <openvino_docs_ov_plugin_dg_compiled_model> object.

2. :doc:Compiled Model class <openvino_docs_ov_plugin_dg_compiled_model>:

   • Is an execution configuration compiled for a particular device and takes into account its capabilities.
   • Holds a reference to a particular device and a task executor for this device.
   • Can create several instances of :doc:Inference Request <openvino_docs_ov_plugin_dg_infer_request>.
   • Can export an internal backend specific graph structure to an output stream.

3. :doc:Inference Request class <openvino_docs_ov_plugin_dg_infer_request>:

   • Runs an inference pipeline serially.
   • Can extract performance counters for an inference pipeline execution profiling.

4. :doc:Asynchronous Inference Request class <openvino_docs_ov_plugin_dg_async_infer_request>:

   • Wraps the :doc:Inference Request <openvino_docs_ov_plugin_dg_infer_request> class and runs pipeline stages in parallel on several task executors based on a device-specific pipeline structure.

5. :doc:Plugin specific properties <openvino_docs_ov_plugin_dg_properties>:

   • Provides the plugin specific properties.

6. :doc:Remote Context <openvino_docs_ov_plugin_dg_remote_context>:

   • Provides the device specific remote context. Context allows to create remote tensors.

7. :doc:Remote Tensor <openvino_docs_ov_plugin_dg_remote_tensor>

   • Provides the device specific remote tensor API and implementation.

.. note::

This documentation is written based on the Template plugin, which demonstrates plugin development details. Find the complete code of the Template, which is fully compilable and up-to-date, at <openvino source dir>/src/plugins/template.

Detailed Guides ###############

• :doc:Build <openvino_docs_ov_plugin_dg_plugin_build> a plugin library using CMake
• Plugin and its components :doc:testing <openvino_docs_ov_plugin_dg_plugin_testing>
• :doc:Quantized networks <openvino_docs_ov_plugin_dg_quantized_models>
• :doc:Low precision transformations <openvino_docs_OV_UG_lpt> guide
• :doc:Writing OpenVINO™ transformations <openvino_docs_transformations> guide

API References ##############

• OpenVINO Plugin API <https://docs.openvino.ai/nightly/groupov_dev_api.html>__
• OpenVINO Transformation API <https://docs.openvino.ai/2022.3/groupie_transformation_api.html>__

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