Merge branch 'openvinotoolkit:master' into quantile

openvinotoolkit · Jan 30, 2025 · dcd43e3 · dcd43e3
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diff --git a/.github/workflows/job_openvino_js.yml b/.github/workflows/job_openvino_js.yml
@@ -62,7 +62,7 @@ jobs:
 
       - name: Setup Node ${{ env.NODE_VERSION }}
         if: runner.os != 'Linux' # Node is already installed in the Docker image
-        uses: actions/setup-node@39370e3970a6d050c480ffad4ff0ed4d3fdee5af # v4.1.0
+        uses: actions/setup-node@1d0ff469b7ec7b3cb9d8673fde0c81c44821de2a # v4.2.0
         with:
           node-version: ${{ env.NODE_VERSION }}
 

diff --git a/.github/workflows/windows_vs2019_release.yml b/.github/workflows/windows_vs2019_release.yml
@@ -205,7 +205,7 @@ jobs:
         working-directory: ${{ env.OPENVINO_JS_LIBS_DIR }}
 
       - name: Setup Node ${{ env.NODE_VERSION }}
-        uses: actions/setup-node@39370e3970a6d050c480ffad4ff0ed4d3fdee5af # v4.1.0
+        uses: actions/setup-node@1d0ff469b7ec7b3cb9d8673fde0c81c44821de2a # v4.2.0
         with:
           node-version: ${{ env.NODE_VERSION }}
 

diff --git a/docs/articles_en/about-openvino.rst b/docs/articles_en/about-openvino.rst
@@ -7,7 +7,7 @@ About OpenVINO
 
    about-openvino/key-features
    about-openvino/performance-benchmarks
-   about-openvino/compatibility-and-support
+   OpenVINO Ecosystem <about-openvino/openvino-ecosystem>
    about-openvino/contributing
    Release Notes <about-openvino/release-notes-openvino>
 
@@ -40,10 +40,10 @@ OpenVINO Ecosystem
 Along with the primary components of model optimization and runtime, the toolkit also includes:
 
 * `Neural Network Compression Framework (NNCF) <https://github.com/openvinotoolkit/nncf>`__ - a tool for enhanced OpenVINO™ inference to get performance boost with minimal accuracy drop.
-* :doc:`Openvino Notebooks <learn-openvino/interactive-tutorials-python>`- Jupyter Python notebook, which demonstrate key features of the toolkit.
+* :doc:`Openvino Notebooks <get-started/learn-openvino/interactive-tutorials-python>`- Jupyter Python notebook, which demonstrate key features of the toolkit.
 * `OpenVINO Model Server <https://github.com/openvinotoolkit/model_server>`__ - a server that enables scalability via a serving microservice.
-* :doc:`OpenVINO Training Extensions  <documentation/openvino-ecosystem/openvino-training-extensions>` – a convenient environment to train Deep Learning models and convert them using the OpenVINO™ toolkit for optimized inference.
-* :doc:`Dataset Management Framework (Datumaro) <documentation/openvino-ecosystem/datumaro>` - a tool to build, transform, and analyze datasets.
+* :doc:`OpenVINO Training Extensions  <about-openvino/openvino-ecosystem/openvino-training-extensions>` – a convenient environment to train Deep Learning models and convert them using the OpenVINO™ toolkit for optimized inference.
+* :doc:`Dataset Management Framework (Datumaro) <about-openvino/openvino-ecosystem/datumaro>` - a tool to build, transform, and analyze datasets.
 
 Community
 ##############################################################

diff --git a/...s_en/documentation/openvino-ecosystem.rst → ..._en/about-openvino/openvino-ecosystem.rst b/...s_en/documentation/openvino-ecosystem.rst → ..._en/about-openvino/openvino-ecosystem.rst
@@ -68,7 +68,7 @@ without the need to convert.
 
 | **OpenVINO Training Extensions**
 | :bdg-link-dark:`Github <https://github.com/openvinotoolkit/training_extensions>`
-  :bdg-link-success:`Overview Page <https://docs.openvino.ai/2025/documentation/openvino-ecosystem/openvino-training-extensions.html>`
+  :bdg-link-success:`Overview Page <https://docs.openvino.ai/2025/about-openvino/openvino-ecosystem/openvino-training-extensions.html>`
 
 A convenient environment to train Deep Learning models and convert them using the OpenVINO™
 toolkit for optimized inference.
@@ -77,7 +77,7 @@ toolkit for optimized inference.
 
 | **OpenVINO Security Addon**
 | :bdg-link-dark:`Github <https://github.com/openvinotoolkit/security_addon>`
-  :bdg-link-success:`User Guide <https://docs.openvino.ai/2025/documentation/openvino-ecosystem/openvino-security-add-on.html>`
+  :bdg-link-success:`User Guide <https://docs.openvino.ai/2025/about-openvino/openvino-ecosystem/openvino-security-add-on.html>`
 
 A solution for Model Developers and Independent Software Vendors to use secure packaging and
 secure model execution.
@@ -86,7 +86,7 @@ secure model execution.
 
 | **Datumaro**
 | :bdg-link-dark:`Github <https://github.com/openvinotoolkit/datumaro>`
-  :bdg-link-success:`Overview Page <https://docs.openvino.ai/2025/documentation/openvino-ecosystem/datumaro.html>`
+  :bdg-link-success:`Overview Page <https://docs.openvino.ai/2025/about-openvino/openvino-ecosystem/datumaro.html>`
 
 A framework and a CLI tool for building, transforming, and analyzing datasets.
 |hr|

diff --git a/...mentation/openvino-ecosystem/datumaro.rst → ...-openvino/openvino-ecosystem/datumaro.rst b/...mentation/openvino-ecosystem/datumaro.rst → ...-openvino/openvino-ecosystem/datumaro.rst
diff --git a/...no-ecosystem/openvino-security-add-on.rst → ...no-ecosystem/openvino-security-add-on.rst b/...no-ecosystem/openvino-security-add-on.rst → ...no-ecosystem/openvino-security-add-on.rst
diff --git a/...penvino-ecosystem/openvino-test-drive.rst → ...penvino-ecosystem/openvino-test-drive.rst b/...penvino-ecosystem/openvino-test-drive.rst → ...penvino-ecosystem/openvino-test-drive.rst
diff --git a/...cosystem/openvino-training-extensions.rst → ...cosystem/openvino-training-extensions.rst b/...cosystem/openvino-training-extensions.rst → ...cosystem/openvino-training-extensions.rst
diff --git a/...ticles_en/about-openvino/performance-benchmarks/getting-performance-numbers.rst b/...ticles_en/about-openvino/performance-benchmarks/getting-performance-numbers.rst
@@ -128,7 +128,7 @@ General considerations
    When comparing OpenVINO Runtime performance with the framework or reference code,
    make sure that both versions are as similar as possible:
 
-   * Wrap the exact inference execution (for examples, see :doc:`Benchmark app <../../learn-openvino/openvino-samples/benchmark-tool>`).
+   * Wrap the exact inference execution (for examples, see :doc:`Benchmark app <../../get-started/learn-openvino/openvino-samples/benchmark-tool>`).
    * Do not include model loading time.
    * Ensure that the inputs are identical for OpenVINO Runtime and the framework. For example, watch out for random values that can be used to populate the inputs.
    * In situations when any user-side pre-processing should be tracked separately, consider :doc:`image pre-processing and conversion <../../openvino-workflow/running-inference/optimize-inference/optimize-preprocessing>`.
@@ -149,7 +149,7 @@ OpenVINO benchmarking (general)
 +++++++++++++++++++++++++++++++
 
 The default way of measuring OpenVINO performance is running a piece of code, referred to as
-:doc:`the benchmark tool <../../learn-openvino/openvino-samples/benchmark-tool>`.
+:doc:`the benchmark tool <../../get-started/learn-openvino/openvino-samples/benchmark-tool>`.
 For Python, it is part of the OpenVINO Runtime installation, while for C++, it is available as
 a code sample.
 
@@ -165,7 +165,7 @@ as:
    benchmark_app -m <model> -d <device> -i <input>
 
 
-Each of the :doc:`OpenVINO supported devices <../compatibility-and-support/supported-devices>`
+Each of the :doc:`OpenVINO supported devices <../../documentation/compatibility-and-support/supported-devices>`
 offers performance settings that contain command-line equivalents in the Benchmark app.
 
 While these settings provide really low-level control for the optimal model performance on a
@@ -186,7 +186,7 @@ Internal Inference Performance Counters and Execution Graphs
 
 More detailed insights into inference performance breakdown can be achieved with device-specific
 performance counters and/or execution graphs.
-Both :doc:`C++ and Python <../../learn-openvino/openvino-samples/benchmark-tool>`
+Both :doc:`C++ and Python <../../get-started/learn-openvino/openvino-samples/benchmark-tool>`
 versions of the benchmark_app support a ``-pc`` command-line parameter that outputs an internal
 execution breakdown.
 

diff --git a/...rticles_en/about-openvino/performance-benchmarks/performance-benchmarks-faq.rst b/...rticles_en/about-openvino/performance-benchmarks/performance-benchmarks-faq.rst
@@ -27,7 +27,7 @@ Performance Information F.A.Q.
 
    All of the performance benchmarks on traditional network models are generated using the
    open-source tool within the Intel® Distribution of OpenVINO™ toolkit
-   called :doc:`benchmark_app <../../learn-openvino/openvino-samples/benchmark-tool>`.
+   called :doc:`benchmark_app <../../get-started/learn-openvino/openvino-samples/benchmark-tool>`.
 
    For diffusers (Stable-Diffusion) and foundational models (aka LLMs) please use the OpenVINO GenAI
    opensource repo `OpenVINO GenAI tools/llm_bench <https://github.com/openvinotoolkit/openvino.genai/tree/master/tools/llm_bench>`__
@@ -97,7 +97,7 @@ Performance Information F.A.Q.
 
    Intel partners with vendors all over the world. For a list of Hardware Manufacturers, see the
    `Intel® AI: In Production Partners & Solutions Catalog <https://www.intel.com/content/www/us/en/internet-of-things/ai-in-production/partners-solutions-catalog.html>`__.
-   For more details, see the :doc:`Supported Devices <../compatibility-and-support/supported-devices>` article.
+   For more details, see the :doc:`Supported Devices <../../documentation/compatibility-and-support/supported-devices>` article.
 
 
 .. dropdown:: How can I optimize my models for better performance or accuracy?

diff --git a/docs/articles_en/documentation.rst b/docs/articles_en/documentation.rst
@@ -13,18 +13,18 @@ Documentation
 
    API Reference <api/api_reference>
    OpenVINO IR format and Operation Sets <documentation/openvino-ir-format>
-   Tool Ecosystem <documentation/openvino-ecosystem>
+   Compatibility and Support <documentation/compatibility-and-support>
+   Legacy Features <documentation/legacy-features>
    OpenVINO Extensibility <documentation/openvino-extensibility>
    OpenVINO™ Security <documentation/openvino-security>
-   Legacy Features <documentation/legacy-features>
 
 
 This section provides reference documents that guide you through the OpenVINO toolkit workflow, from preparing models, optimizing them, to deploying them in your own deep learning applications.
 
 | :doc:`API Reference doc path <api/api_reference>`
 | A collection of reference articles for OpenVINO C++, C, and Python APIs.
 
-| :doc:`OpenVINO Ecosystem <documentation/openvino-ecosystem>`
+| :doc:`OpenVINO Ecosystem <about-openvino/openvino-ecosystem>`
 | Apart from the core components, OpenVINO offers tools, plugins, and expansions revolving around it, even if not constituting necessary parts of its workflow. This section gives you an overview of what makes up the OpenVINO toolkit.
 
 | :doc:`OpenVINO Extensibility Mechanism <documentation/openvino-extensibility>`

diff --git a/...ut-openvino/compatibility-and-support.rst → ...cumentation/compatibility-and-support.rst b/...ut-openvino/compatibility-and-support.rst → ...cumentation/compatibility-and-support.rst
diff --git a/...ibility-and-support/supported-devices.rst → ...ibility-and-support/supported-devices.rst b/...ibility-and-support/supported-devices.rst → ...ibility-and-support/supported-devices.rst
@@ -13,7 +13,7 @@ deep learning models:
 :doc:`NPU <../../openvino-workflow/running-inference/inference-devices-and-modes/npu-device>`.
 
 | For their usage guides, see :doc:`Devices and Modes <../../openvino-workflow/running-inference/inference-devices-and-modes>`.
-| For a detailed list of devices, see :doc:`System Requirements <../release-notes-openvino/system-requirements>`.
+| For a detailed list of devices, see :doc:`System Requirements <../../about-openvino/release-notes-openvino/system-requirements>`.
 
 
 Beside running inference with a specific device,
@@ -43,7 +43,7 @@ Feature Support and API Coverage
  :doc:`Multi-stream execution <../../openvino-workflow/running-inference/optimize-inference/optimizing-throughput>`                       Yes     Yes        No
  :doc:`Model caching <../../openvino-workflow/running-inference/optimize-inference/optimizing-latency/model-caching-overview>`            Yes     Partial    Yes
  :doc:`Dynamic shapes <../../openvino-workflow/running-inference/dynamic-shapes>`                                                         Yes     Partial    No
- :doc:`Import/Export <../../documentation/openvino-ecosystem>`                                                                            Yes     Yes        Yes
+ :doc:`Import/Export <../../about-openvino/openvino-ecosystem>`                                                                            Yes     Yes        Yes
  :doc:`Preprocessing acceleration <../../openvino-workflow/running-inference/optimize-inference/optimize-preprocessing>`                  Yes     Yes        No
  :doc:`Stateful models <../../openvino-workflow/running-inference/stateful-models>`                                                       Yes     Yes        Yes
  :doc:`Extensibility <../../documentation/openvino-extensibility>`                                                                        Yes     Yes        No

diff --git a/...ity-and-support/supported-models-onnx.rst → ...ity-and-support/supported-models-onnx.rst b/...ity-and-support/supported-models-onnx.rst → ...ity-and-support/supported-models-onnx.rst
diff --git a/...tibility-and-support/supported-models.rst → ...tibility-and-support/supported-models.rst b/...tibility-and-support/supported-models.rst → ...tibility-and-support/supported-models.rst
diff --git a/...lity-and-support/supported-operations.rst → ...lity-and-support/supported-operations.rst b/...lity-and-support/supported-operations.rst → ...lity-and-support/supported-operations.rst
diff --git a/docs/articles_en/documentation/openvino-extensibility.rst b/docs/articles_en/documentation/openvino-extensibility.rst
@@ -25,7 +25,7 @@ OpenVINO Extensibility Mechanism
 
 The Intel® Distribution of OpenVINO™ toolkit supports neural-network models trained with various frameworks, including
 TensorFlow, PyTorch, ONNX, TensorFlow Lite, and PaddlePaddle. The list of supported operations is different for each of the supported frameworks.
-To see the operations supported by your framework, refer to :doc:`Supported Framework Operations <../about-openvino/compatibility-and-support/supported-operations>`.
+To see the operations supported by your framework, refer to :doc:`Supported Framework Operations <../documentation/compatibility-and-support/supported-operations>`.
 
 Custom operations, which are not included in the list, are not recognized by OpenVINO out-of-the-box. The need for custom operation may appear in two cases:
 
@@ -187,6 +187,6 @@ See Also
 ########
 
 * :doc:`OpenVINO Transformations <openvino-extensibility/transformation-api>`
-* :doc:`Using OpenVINO Runtime Samples <../learn-openvino/openvino-samples>`
-* :doc:`Hello Shape Infer SSD sample <../learn-openvino/openvino-samples/hello-reshape-ssd>`
+* :doc:`Using OpenVINO Runtime Samples <../get-started/learn-openvino/openvino-samples>`
+* :doc:`Hello Shape Infer SSD sample <../get-started/learn-openvino/openvino-samples/hello-reshape-ssd>`
 
diff --git a/...ility/openvino-plugin-library/advanced-guides/low-precision-transformations.rst b/...ility/openvino-plugin-library/advanced-guides/low-precision-transformations.rst
@@ -322,7 +322,7 @@ redistributed in the "Saved model" format, converted to a frozen graph using the
 Inference
 +++++++++
 
-The simplest way to infer the model and collect performance counters is :doc:`Benchmark Application <../../../../learn-openvino/openvino-samples/benchmark-tool>`.
+The simplest way to infer the model and collect performance counters is :doc:`Benchmark Application <../../../../get-started/learn-openvino/openvino-samples/benchmark-tool>`.
 
 .. code-block:: sh
 

diff --git a/docs/articles_en/documentation/openvino-security.rst b/docs/articles_en/documentation/openvino-security.rst
@@ -8,7 +8,7 @@ with encryption or other security tools.
 Actual security and privacy requirements depend on your unique deployment scenario.
 This section provides general guidance on using OpenVINO tools and libraries securely.
 The main security measure for OpenVINO is its
-:doc:`Security Add-on <openvino-ecosystem/openvino-security-add-on>`. You can find its description
+:doc:`Security Add-on <../about-openvino/openvino-ecosystem/openvino-security-add-on>`. You can find its description
 in the Ecosystem section.
 
 .. _encrypted-models:
@@ -86,4 +86,4 @@ Additional Resources
 - Intel® Distribution of OpenVINO™ toolkit `home page <https://software.intel.com/en-us/openvino-toolkit>`__.
 - :doc:`Convert a Model <../openvino-workflow/model-preparation/convert-model-to-ir>`.
 - :doc:`OpenVINO™ Runtime User Guide <../openvino-workflow/running-inference>`.
-- For more information on Sample Applications, see the :doc:`OpenVINO Samples Overview <../learn-openvino/openvino-samples>`
+- For more information on Sample Applications, see the :doc:`OpenVINO Samples Overview <../get-started/learn-openvino/openvino-samples>`
diff --git a/docs/articles_en/get-started.rst b/docs/articles_en/get-started.rst
@@ -12,6 +12,7 @@ GET STARTED
    :hidden:
 
    Install OpenVINO <get-started/install-openvino>
+   Learn OpenVINO <get-started/learn-openvino>
    System Requirements <./about-openvino/release-notes-openvino/system-requirements>
 
 
@@ -67,7 +68,7 @@ Learn the basics of working with models and inference in OpenVINO. Begin with
 Interactive Tutorials - Jupyter Notebooks
 -----------------------------------------
 
-Start with :doc:`interactive Python <learn-openvino/interactive-tutorials-python>` that show the basics of model inference, the OpenVINO API, how to convert models to OpenVINO format, and more.
+Start with :doc:`interactive Python <get-started/learn-openvino/interactive-tutorials-python>` that show the basics of model inference, the OpenVINO API, how to convert models to OpenVINO format, and more.
 
 * `Hello Image Classification <notebooks/hello-world-with-output.html>`__ - Load an image classification model in OpenVINO and use it to apply a label to an image
 * `OpenVINO Runtime API Tutorial <notebooks/openvino-api-with-output.html>`__ - Learn the basic Python API for working with models in OpenVINO
@@ -79,7 +80,7 @@ Start with :doc:`interactive Python <learn-openvino/interactive-tutorials-python
 OpenVINO Code Samples
 ---------------------
 
-View :doc:`sample code <learn-openvino/openvino-samples>` for various C++ and Python applications that can be used as a starting point for your own application. For C++ developers, step through the :doc:`Get Started with C++ Samples <learn-openvino/openvino-samples/get-started-demos>` to learn how to build and run an image classification program that uses OpenVINO’s C++ API.
+View :doc:`sample code <get-started/learn-openvino/openvino-samples>` for various C++ and Python applications that can be used as a starting point for your own application. For C++ developers, step through the :doc:`Get Started with C++ Samples <get-started/learn-openvino/openvino-samples/get-started-demos>` to learn how to build and run an image classification program that uses OpenVINO’s C++ API.
 
 .. _integrate-openvino:
 
@@ -120,7 +121,7 @@ Pipeline and model configuration features in OpenVINO Runtime allow you to easil
 * :doc:`Automatic Batching <openvino-workflow/running-inference/inference-devices-and-modes/automatic-batching>` performs on-the-fly grouping of inference requests to maximize utilization of the target hardware’s memory and processing cores.
 * :doc:`Performance Hints <openvino-workflow/running-inference/optimize-inference/high-level-performance-hints>` automatically adjust runtime parameters to prioritize for low latency or high throughput
 * :doc:`Dynamic Shapes <openvino-workflow/running-inference/dynamic-shapes>` reshapes models to accept arbitrarily-sized inputs, increasing flexibility for applications that encounter different data shapes
-* :doc:`Benchmark Tool <learn-openvino/openvino-samples/benchmark-tool>` characterizes model performance in various hardware and pipeline configurations
+* :doc:`Benchmark Tool <get-started/learn-openvino/openvino-samples/benchmark-tool>` characterizes model performance in various hardware and pipeline configurations
 
 .. _additional-about-openvino/additional-resources:
 

diff --git a/docs/articles_en/get-started/install-openvino/configurations.rst b/docs/articles_en/get-started/install-openvino/configurations.rst
@@ -15,6 +15,7 @@ Additional Configurations
    For GPU <configurations/configurations-intel-gpu>
    For NPU <configurations/configurations-intel-npu>
    GenAI Dependencies <configurations/genai-dependencies>
+   Troubleshooting Guide for OpenVINO™ Installation & Configuration <troubleshooting-install-config.html>
 
 For certain use cases, you may need to install additional software, to benefit from the full
 potential of OpenVINO™. Check the following list for components used in your workflow:

diff --git a/docs/articles_en/get-started/install-openvino/install-openvino-apt.rst b/docs/articles_en/get-started/install-openvino/install-openvino-apt.rst
@@ -156,7 +156,7 @@ need to install additional components. Check the
 to see if your case needs any of them.
 
 With the APT distribution, you can build OpenVINO sample files, as explained in the
-:doc:`guide for OpenVINO sample applications <../../../learn-openvino/openvino-samples>`.
+:doc:`guide for OpenVINO sample applications <../../../get-started/learn-openvino/openvino-samples>`.
 For C++ and C, just run the ``build_samples.sh`` script:
 
 .. tab-set::
@@ -215,23 +215,23 @@ What's Next?
 Now that you've installed OpenVINO Runtime, you're ready to run your own machine learning applications!
 Learn more about how to integrate a model in OpenVINO applications by trying out the following tutorials:
 
-* Try the :doc:`C++ Quick Start Example <../../../learn-openvino/openvino-samples/get-started-demos>` for step-by-step
+* Try the :doc:`C++ Quick Start Example <../../../get-started/learn-openvino/openvino-samples/get-started-demos>` for step-by-step
   instructions on building and running a basic image classification C++ application.
 
   .. image:: https://user-images.githubusercontent.com/36741649/127170593-86976dc3-e5e4-40be-b0a6-206379cd7df5.jpg
      :width: 400
 
 * Visit the :ref:`Samples <code samples>` page for other C++ example applications to get you started with OpenVINO, such as:
 
-  * :doc:`Basic object detection with the Hello Reshape SSD C++ sample <../../../learn-openvino/openvino-samples/hello-reshape-ssd>`
-  * :doc:`Object classification sample <../../../learn-openvino/openvino-samples/hello-classification>`
+  * :doc:`Basic object detection with the Hello Reshape SSD C++ sample <../../../get-started/learn-openvino/openvino-samples/hello-reshape-ssd>`
+  * :doc:`Object classification sample <../../../get-started/learn-openvino/openvino-samples/hello-classification>`
 
 You can also try the following:
 
 * Learn more about :doc:`OpenVINO Workflow <../../../openvino-workflow>`.
 * To prepare your models for working with OpenVINO, see :doc:`Model Preparation <../../../openvino-workflow/model-preparation>`.
 * See pre-trained deep learning models on `Hugging Face <https://huggingface.co/OpenVINO>`__
 * Learn more about :doc:`Inference with OpenVINO Runtime <../../../openvino-workflow/running-inference>`.
-* See sample applications in :doc:`OpenVINO toolkit Samples Overview <../../../learn-openvino/openvino-samples>`.
+* See sample applications in :doc:`OpenVINO toolkit Samples Overview <../../../get-started/learn-openvino/openvino-samples>`.
 * Take a glance at the OpenVINO `product home page <https://software.intel.com/en-us/openvino-toolkit>`__ .