Merge branch 'openvinotoolkit:master' into softmax_cross_entropy_loss…

…_for_onnx_fe

.github/scripts/workflow_rerun/errors_to_look_for.json

@@ -118,5 +118,13 @@
     {
         "error_text": "file DOWNLOAD cannot compute hash on failed download",
         "ticket": 156593
+    },
+    {
+        "error_text": "lost communication with the server",
+        "ticket": 160816
+    },
+    {
+        "error_text": "the runner has received a shutdown signal",
+        "ticket": 160818
     }
 ]

.github/workflows/build_doc.yml

@@ -78,13 +78,13 @@ jobs:
           echo "PR_NUMBER=$PR_NUMBER" >> $GITHUB_ENV
 
       - name: 'Upload sphinx.log'
-        uses: actions/upload-artifact@b4b15b8c7c6ac21ea08fcf65892d2ee8f75cf882 # v4.4.3
+        uses: actions/upload-artifact@65c4c4a1ddee5b72f698fdd19549f0f0fb45cf08 # v4.6.0
         with:
           name: sphinx_build_log_${{ env.PR_NUMBER }}.log
           path: build/docs/sphinx.log
 
       - name: 'Upload docs html'
-        uses: actions/upload-artifact@b4b15b8c7c6ac21ea08fcf65892d2ee8f75cf882 # v4.4.3
+        uses: actions/upload-artifact@65c4c4a1ddee5b72f698fdd19549f0f0fb45cf08 # v4.6.0
         with:
           name: openvino_docs_html_${{ env.PR_NUMBER }}.zip
           path: build/docs/openvino_docs_html.zip
@@ -101,7 +101,7 @@ jobs:
 
       - name: 'Upload test results'
         if: failure()
-        uses: actions/upload-artifact@b4b15b8c7c6ac21ea08fcf65892d2ee8f75cf882 # v4.4.3
+        uses: actions/upload-artifact@65c4c4a1ddee5b72f698fdd19549f0f0fb45cf08 # v4.6.0
         with:
           name: openvino_docs_pytest
           path: build/docs/_artifacts/

.github/workflows/stale_prs_and_issues.yml

@@ -14,7 +14,7 @@ jobs:
     runs-on: ubuntu-latest
     if: ${{ github.repository_owner == 'openvinotoolkit' }}
     steps:
-      - uses: actions/stale@28ca1036281a5e5922ead5184a1bbf96e5fc984e # v9.0.0
+      - uses: actions/stale@5bef64f19d7facfb25b37b414482c7164d639639 # v9.1.0
         with:
           stale-issue-message: 'This issue will be closed in a week because of 9 months of no activity.'
           stale-pr-message: 'This PR will be closed in a week because of 2 weeks of no activity.'

.github/workflows/workflow_rerunner.yml

@@ -29,7 +29,7 @@ jobs:
     name: Rerun Workflow
     # Run only for the failed workflows in openvinotoolkit org
     if: ${{ github.event.workflow_run.conclusion == 'failure' && github.repository_owner == 'openvinotoolkit' }}
-    runs-on: aks-linux-2-cores-8gb-stats
+    runs-on: aks-linux-smallworker
     permissions:
       actions: write
       contents: read

CMakeLists.txt

@@ -48,7 +48,7 @@ endif()
 
 project(OpenVINO
         DESCRIPTION "OpenVINO toolkit"
-        HOMEPAGE_URL "https://docs.openvino.ai/2024/home.html"
+        HOMEPAGE_URL "https://docs.openvino.ai/2025/index.html"
         LANGUAGES C CXX)
 
 find_package(OpenVINODeveloperScripts REQUIRED

CONTRIBUTING.md

@@ -52,7 +52,7 @@ product better.
      Since the market of computing devices is constantly evolving, OpenVINO is always open to extending
      its support for new hardware. If you want to run inference on a device that is currently not supported,
      you can see how to develop a new plugin for it in the
-     [Plugin Developer Guide](https://docs.openvino.ai/2024/documentation/openvino-extensibility/openvino-plugin-library.html).
+     [Plugin Developer Guide](https://docs.openvino.ai/2025/documentation/openvino-extensibility/openvino-plugin-library.html).
 
 
 ### Improve documentation

README.md

@@ -6,7 +6,7 @@ Open-source software toolkit for optimizing and deploying deep learning models.
 </h3>
 
 <p align="center">
- <a href="https://docs.openvino.ai/2024/index.html"><b>Documentation</b></a> • <a href="https://blog.openvino.ai"><b>Blog</b></a> • <a href="https://docs.openvino.ai/2024/about-openvino/key-features.html"><b>Key Features</b></a> • <a href="https://docs.openvino.ai/2024/learn-openvino.html"><b>Tutorials</b></a> • <a href="https://docs.openvino.ai/2024/documentation/openvino-ecosystem.html"><b>Integrations</b></a> • <a href="https://docs.openvino.ai/2024/about-openvino/performance-benchmarks.html"><b>Benchmarks</b></a> • <a href="https://github.com/openvinotoolkit/openvino.genai"><b>Generative AI</b></a>
+ <a href="https://docs.openvino.ai/2025/index.html"><b>Documentation</b></a> • <a href="https://blog.openvino.ai"><b>Blog</b></a> • <a href="https://docs.openvino.ai/2025/about-openvino/key-features.html"><b>Key Features</b></a> • <a href="https://docs.openvino.ai/2025/learn-openvino.html"><b>Tutorials</b></a> • <a href="https://docs.openvino.ai/2025/documentation/openvino-ecosystem.html"><b>Integrations</b></a> • <a href="https://docs.openvino.ai/2025/about-openvino/performance-benchmarks.html"><b>Benchmarks</b></a> • <a href="https://github.com/openvinotoolkit/openvino.genai"><b>Generative AI</b></a>
 </p>
 
 [![PyPI Status](https://badge.fury.io/py/openvino.svg)](https://badge.fury.io/py/openvino)
@@ -24,22 +24,22 @@ Open-source software toolkit for optimizing and deploying deep learning models.
 - **Broad Platform Compatibility**: Reduce resource demands and efficiently deploy on a range of platforms from edge to cloud. OpenVINO™ supports inference on CPU (x86, ARM), GPU (OpenCL capable, integrated and discrete) and AI accelerators (Intel NPU).
 - **Community and Ecosystem**: Join an active community contributing to the enhancement of deep learning performance across various domains.
 
-Check out the [OpenVINO Cheat Sheet](https://docs.openvino.ai/2024/_static/download/OpenVINO_Quick_Start_Guide.pdf) and [Key Features](https://docs.openvino.ai/2024/about-openvino/key-features.html) for a quick reference.
+Check out the [OpenVINO Cheat Sheet](https://docs.openvino.ai/2025/_static/download/OpenVINO_Quick_Start_Guide.pdf) and [Key Features](https://docs.openvino.ai/2025/about-openvino/key-features.html) for a quick reference.
 
 
 ## Installation
 
-[Get your preferred distribution of OpenVINO](https://docs.openvino.ai/2024/get-started/install-openvino.html) or use this command for quick installation:
+[Get your preferred distribution of OpenVINO](https://docs.openvino.ai/2025/get-started/install-openvino.html) or use this command for quick installation:
 
 ```sh
 pip install -U openvino
 ```
 
-Check [system requirements](https://docs.openvino.ai/2024/about-openvino/system-requirements.html) and [supported devices](https://docs.openvino.ai/2024/about-openvino/compatibility-and-support/supported-devices.html) for detailed information.
+Check [system requirements](https://docs.openvino.ai/2025/about-openvino/system-requirements.html) and [supported devices](https://docs.openvino.ai/2025/about-openvino/compatibility-and-support/supported-devices.html) for detailed information.
 
 ## Tutorials and Examples
 
-[OpenVINO Quickstart example](https://docs.openvino.ai/2024/get-started.html) will walk you through the basics of deploying your first model.
+[OpenVINO Quickstart example](https://docs.openvino.ai/2025/get-started.html) will walk you through the basics of deploying your first model.
 
 Learn how to optimize and deploy popular models with the [OpenVINO Notebooks](https://github.com/openvinotoolkit/openvino_notebooks)📚:
 - [Create an LLM-powered Chatbot using OpenVINO](https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/llm-chatbot/llm-chatbot-generate-api.ipynb)
@@ -48,7 +48,7 @@ Learn how to optimize and deploy popular models with the [OpenVINO Notebooks](ht
 - [Multimodal assistant with LLaVa and OpenVINO](https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/llava-multimodal-chatbot/llava-multimodal-chatbot-genai.ipynb)
 - [Automatic speech recognition using Whisper and OpenVINO](https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/whisper-asr-genai/whisper-asr-genai.ipynb)
 
-Discover more examples in the [OpenVINO Samples (Python & C++)](https://docs.openvino.ai/2024/learn-openvino/openvino-samples.html) and [Notebooks (Python)](https://docs.openvino.ai/2024/learn-openvino/interactive-tutorials-python.html).
+Discover more examples in the [OpenVINO Samples (Python & C++)](https://docs.openvino.ai/2025/learn-openvino/openvino-samples.html) and [Notebooks (Python)](https://docs.openvino.ai/2025/learn-openvino/interactive-tutorials-python.html).
 
 Here are easy-to-follow code examples demonstrating how to run PyTorch and TensorFlow model inference using OpenVINO:
 
@@ -96,11 +96,11 @@ data = np.random.rand(1, 224, 224, 3)
 output = compiled_model({0: data})
 ```
 
-OpenVINO supports the CPU, GPU, and NPU [devices](https://docs.openvino.ai/2024/openvino-workflow/running-inference/inference-devices-and-modes.html) and works with models from PyTorch, TensorFlow, ONNX, TensorFlow Lite, PaddlePaddle, and JAX/Flax [frameworks](https://docs.openvino.ai/2024/openvino-workflow/model-preparation.html). It includes [APIs](https://docs.openvino.ai/2024/api/api_reference.html) in C++, Python, C, NodeJS, and offers the GenAI API for optimized model pipelines and performance.
+OpenVINO supports the CPU, GPU, and NPU [devices](https://docs.openvino.ai/2025/openvino-workflow/running-inference/inference-devices-and-modes.html) and works with models from PyTorch, TensorFlow, ONNX, TensorFlow Lite, PaddlePaddle, and JAX/Flax [frameworks](https://docs.openvino.ai/2025/openvino-workflow/model-preparation.html). It includes [APIs](https://docs.openvino.ai/2025/api/api_reference.html) in C++, Python, C, NodeJS, and offers the GenAI API for optimized model pipelines and performance.
 
 ## Generative AI with OpenVINO
 
-Get started with the OpenVINO GenAI [installation](https://docs.openvino.ai/2024/get-started/install-openvino/install-openvino-genai.html) and refer to the [detailed guide](https://docs.openvino.ai/2024/openvino-workflow-generative/generative-inference.html) to explore the capabilities of Generative AI using OpenVINO.
+Get started with the OpenVINO GenAI [installation](https://docs.openvino.ai/2025/get-started/install-openvino/install-openvino-genai.html) and refer to the [detailed guide](https://docs.openvino.ai/2025/openvino-workflow-generative/generative-inference.html) to explore the capabilities of Generative AI using OpenVINO.
 
 Learn how to run LLMs and GenAI with [Samples](https://github.com/openvinotoolkit/openvino.genai/tree/master/samples) in the [OpenVINO™ GenAI repo](https://github.com/openvinotoolkit/openvino.genai). See GenAI in action with Jupyter notebooks: [LLM-powered Chatbot](https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/llm-chatbot/README.md) and [LLM Instruction-following pipeline](https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/llm-question-answering/README.md).
 
@@ -122,7 +122,7 @@ Learn how to run LLMs and GenAI with [Samples](https://github.com/openvinotoolki
 ### Integrations
 
 -   [🤗Optimum Intel](https://github.com/huggingface/optimum-intel) - grab and use models leveraging OpenVINO within the Hugging Face API.
--   [Torch.compile](https://docs.openvino.ai/2024/openvino-workflow/torch-compile.html) - use OpenVINO for Python-native applications by JIT-compiling code into optimized kernels.
+-   [Torch.compile](https://docs.openvino.ai/2025/openvino-workflow/torch-compile.html) - use OpenVINO for Python-native applications by JIT-compiling code into optimized kernels.
 -   [OpenVINO LLMs inference and serving with vLLM​](https://docs.vllm.ai/en/stable/getting_started/openvino-installation.html) - enhance vLLM's fast and easy model serving with the OpenVINO backend.
 -   [OpenVINO Execution Provider for ONNX Runtime](https://onnxruntime.ai/docs/execution-providers/OpenVINO-ExecutionProvider.html) - use OpenVINO as a backend with your existing ONNX Runtime code.
 -   [LlamaIndex](https://docs.llamaindex.ai/en/stable/examples/llm/openvino/) - build context-augmented GenAI applications with the LlamaIndex framework and enhance runtime performance with OpenVINO.
@@ -133,7 +133,7 @@ Check out the [Awesome OpenVINO](https://github.com/openvinotoolkit/awesome-open
 
 ## Performance
 
-Explore [OpenVINO Performance Benchmarks](https://docs.openvino.ai/2024/about-openvino/performance-benchmarks.html) to discover the optimal hardware configurations and plan your AI deployment based on verified data.
+Explore [OpenVINO Performance Benchmarks](https://docs.openvino.ai/2025/about-openvino/performance-benchmarks.html) to discover the optimal hardware configurations and plan your AI deployment based on verified data.
 
 ## Contribution and Support
 
@@ -149,7 +149,7 @@ You can ask questions and get support on:
 
 ## Resources
 
-* [Release Notes](https://docs.openvino.ai/2024/about-openvino/release-notes-openvino.html)
+* [Release Notes](https://docs.openvino.ai/2025/about-openvino/release-notes-openvino.html)
 * [OpenVINO Blog](https://blog.openvino.ai/)
 * [OpenVINO™ toolkit on Medium](https://medium.com/@openvino)
 
@@ -164,7 +164,7 @@ You can opt-out at any time by running the command:
 opt_in_out --opt_out
 ```
 
-More Information is available at [OpenVINO™ Telemetry](https://docs.openvino.ai/2024/about-openvino/additional-resources/telemetry.html).
+More Information is available at [OpenVINO™ Telemetry](https://docs.openvino.ai/2025/about-openvino/additional-resources/telemetry.html).
 
 ## License
 

docs/RELEASE.MD

@@ -13,7 +13,7 @@ This phase takes 2-4 weeks and involves scoping the backlog, prioritizing it, an
 
 ### Execution (development of new features)
 - [OpenVINO Contributing Guide](https://github.com/openvinotoolkit/openvino/blob/master/CONTRIBUTING.md)
-- [Code Contribution Guide](https://docs.openvino.ai/2024/about-openvino/contributing/code-contribution-guide.html)
+- [Code Contribution Guide](https://docs.openvino.ai/2025/about-openvino/contributing/code-contribution-guide.html)
 - [OpenVINO First Good Issue](https://github.com/openvinotoolkit/openvino/issues/17502)
 
 ### Stabilization (Feature Freeze, Code Freeze milestones)
@@ -25,5 +25,5 @@ This phase takes 2-4 weeks and involves scoping the backlog, prioritizing it, an
 - After Code Freeze, the testing team can perform final regression testing to ensure that recent changes have not introduced new bugs and that the software meets the required quality standards.
 
 ### Distribution
-- OpenVINO has different types of build distribution: Regular releases, Long-Term Support, Pre-release releases, Nightly builds. Read more here: [OpenVINO Release Policy](https://docs.openvino.ai/2024/about-openvino/release-notes-openvino/release-policy.html)
+- OpenVINO has different types of build distribution: Regular releases, Long-Term Support, Pre-release releases, Nightly builds. Read more here: [OpenVINO Release Policy](https://docs.openvino.ai/2025/about-openvino/release-notes-openvino/release-policy.html)
 - Different distribution channels are supported. Explore different options here: [OpenVINO Download](https://www.intel.com/content/www/us/en/developer/tools/openvino-toolkit/download.html)

docs/articles_en/about-openvino/contributing.rst

@@ -89,7 +89,7 @@ PR. This way, it will be easier for other developers to track changes.
 
 If you want to run inference on a device that is currently not supported, you
 can see how to develop a new plugin for it in the
-`Plugin Developer Guide <https://docs.openvino.ai/nightly/documentation/openvino-extensibility/openvino-plugin-library.html>`__.
+`Plugin Developer Guide <https://docs.openvino.ai/2025/documentation/openvino-extensibility/openvino-plugin-library.html>`__.
 
 
 :fas:`file-alt` Improve documentation

docs/articles_en/about-openvino/key-features.rst

@@ -17,7 +17,7 @@ Easy Integration
 |     With the OpenVINO GenAI, you can run generative models with just a few lines of code.
       Check out the GenAI guide for instructions on how to do it.
 
-| `Python / C++ / C / NodeJS APIs <https://docs.openvino.ai/2024/api/api_reference.html>`__
+| `Python / C++ / C / NodeJS APIs <https://docs.openvino.ai/2025/api/api_reference.html>`__
 |     OpenVINO offers the C++ API as a complete set of available methods. For less resource-critical
       solutions, the Python API provides almost full coverage, while C and NodeJS ones are limited
       to the methods most basic for their typical environments. The NodeJS API, is still in its

docs/articles_en/about-openvino/performance-benchmarks/generative-ai-performance.rst

@@ -56,7 +56,7 @@ The tables below list the key performance indicators for inference on built-in G
 
    .. grid-item::
 
-      .. button-link:: https://docs.openvino.ai/2024/_static/download/benchmarking_genai_platform_list.pdf
+      .. button-link:: https://docs.openvino.ai/2025/_static/download/benchmarking_genai_platform_list.pdf
          :color: primary
          :outline:
          :expand:

docs/articles_en/about-openvino/release-notes-openvino/system-requirements.rst

@@ -93,13 +93,12 @@ Intel® Neural Processing Unit
 
    .. tab-item:: Additional considerations
 
-      * These Accelerators require :doc:`drivers <../../get-started/configurations/configurations-intel-npu>`
+      * These Accelerators require :doc:`drivers <../../get-started/install-openvino/configurations/configurations-intel-npu>`
         that are not included in the Intel® Distribution of OpenVINO™ toolkit package.
       * Users can access the NPU plugin through the OpenVINO archives on
         the :doc:`download page <../../get-started/install-openvino>`.
 
 
-
 Operating systems and developer environment
 #######################################################
 

docs/articles_en/documentation/openvino-ecosystem.rst

@@ -33,7 +33,7 @@ models. Check the LLM-powered Chatbot Jupyter notebook to see how GenAI works.
 
 | **Neural Network Compression Framework**
 | :bdg-link-dark:`Github <https://github.com/openvinotoolkit/nncf>`
-  :bdg-link-success:`User Guide <https://docs.openvino.ai/2024/openvino-workflow/model-optimization.html>`
+  :bdg-link-success:`User Guide <https://docs.openvino.ai/2025/openvino-workflow/model-optimization.html>`
 
 A suite of advanced algorithms for Neural Network inference optimization with minimal accuracy
 drop. NNCF applies quantization, filter pruning, binarization, and sparsity algorithms to PyTorch
@@ -43,7 +43,7 @@ and TensorFlow models during training.
 
 | **OpenVINO Model Server**
 | :bdg-link-dark:`Github <https://github.com/openvinotoolkit/model_server>`
-  :bdg-link-success:`User Guide <https://docs.openvino.ai/2024/ovms_what_is_openvino_model_server.html>`
+  :bdg-link-success:`User Guide <https://docs.openvino.ai/2025/ovms_what_is_openvino_model_server.html>`
 
 A high-performance system that can be used to access the host models via request to the model
 server.
@@ -52,7 +52,7 @@ server.
 
 | **OpenVINO Notebooks**
 | :bdg-link-dark:`Github <https://github.com/openvinotoolkit/openvino_notebooks>`
-  :bdg-link-success:`Jupyter Notebook Collection <https://docs.openvino.ai/2024/learn-openvino/interactive-tutorials-python.html>`
+  :bdg-link-success:`Jupyter Notebook Collection <https://docs.openvino.ai/2025/learn-openvino/interactive-tutorials-python.html>`
 
 A collection of Jupyter notebooks for learning and experimenting with the OpenVINO™ Toolkit.
 |hr|
@@ -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/2024/documentation/openvino-ecosystem/openvino-training-extensions.html>`
+  :bdg-link-success:`Overview Page <https://docs.openvino.ai/2025/documentation/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/2024/documentation/openvino-ecosystem/openvino-security-add-on.html>`
+  :bdg-link-success:`User Guide <https://docs.openvino.ai/2025/documentation/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/2024/documentation/openvino-ecosystem/datumaro.html>`
+  :bdg-link-success:`Overview Page <https://docs.openvino.ai/2025/documentation/openvino-ecosystem/datumaro.html>`
 
 A framework and a CLI tool for building, transforming, and analyzing datasets.
 |hr|