Merge branch 'openvinotoolkit:master' into hunyuan_model

.github/components.yml

@@ -110,7 +110,6 @@ IR_FE:
 
 ONNX_FE:
   revalidate:
-    - MO
     - OVC
     - ONNX_RT
   build:
@@ -119,15 +118,13 @@ ONNX_FE:
 
 PDPD_FE:
   revalidate:
-    - MO
     - OVC
   build:
     - CPU
     - Python_API
 
 TF_FE:
   revalidate:
-    - MO
     - OVC
   build:
     - CPU
@@ -136,15 +133,13 @@ TF_FE:
 
 TFL_FE:
   revalidate:
-    - MO
     - OVC
   build:
     - CPU
     - Python_API
 
 PyTorch_FE:
   revalidate:
-    - MO
     - OVC
   build:
     - CPU
@@ -153,7 +148,6 @@ PyTorch_FE:
 
 JAX_FE:
   revalidate:
-    - MO
     - OVC
   build:
     - CPU
@@ -171,7 +165,6 @@ C_API:
 Python_API:
   revalidate:
     - samples
-    - MO
     - OVC
     - tools
     - TF_FE
@@ -228,14 +221,6 @@ OVC:
     - Python_API
     - TOKENIZERS # TF_FE tests depends on tokenizers build
 
-MO:
-  revalidate:
-    - PyTorch_FE
-    - TF_FE
-  build:
-    - Python_API
-    - TOKENIZERS # TF_FE tests depends on tokenizers build
-
 tools:
   build:
     - CPU

.github/github_org_control/config.json

@@ -36,7 +36,6 @@
         "openvino-tf-frontend-maintainers": "category: TF FE",
         "openvino-onnx-frontend-maintainers": "category: ONNX FE",
         "openvino-ie-tests-maintainers": "category: IE Tests",
-        "openvino-mo-maintainers": "category: MO",
         "openvino-ovc-maintainers": "category: OVC",
         "openvino-ngraph-maintainers": "category: Core",
         "openvino-scripts-maintainers": "category: build",

.github/workflows/job_python_unit_tests.yml

@@ -133,11 +133,11 @@ jobs:
             --ignore=${INSTALL_TEST_DIR}/onnx/test_python/test_zoo_models.py
 
       - name: OVC unit tests
-        if: fromJSON(inputs.affected-components).MO.test
+        if: fromJSON(inputs.affected-components).OVC.test
         run: python3 -m pytest -s ${INSTALL_TEST_DIR}/ovc/unit_tests --junitxml=${INSTALL_TEST_DIR}/TEST-OpenVinoConversion.xml
 
       - name: OVC Python API Tests
-        if: fromJSON(inputs.affected-components).MO.test
+        if: fromJSON(inputs.affected-components).OVC.test
         run: |
           # Import 'test_utils' installed in '<package_test>/tests/python/openvino'
           export PYTHONPATH=${INSTALL_TEST_DIR}/python

.github/workflows/linux_riscv.yml

@@ -139,7 +139,6 @@ jobs:
             git submodule update --init -- ${OPENVINO_REPO}/thirdparty/gflags
             git submodule update --init -- ${OPENVINO_REPO}/thirdparty/telemetry
             git submodule update --init -- ${OPENVINO_REPO}/src/plugins/intel_cpu
-            git submodule update --init -- ${OPENVINO_REPO}/thirdparty/open_model_zoo
             git submodule update --init -- ${OPENVINO_REPO}/thirdparty/flatbuffers/flatbuffers
           popd
 

.github/workflows/windows_vs2019_release.yml

@@ -358,7 +358,7 @@ jobs:
           --ignore=${{ env.INSTALL_TEST_DIR }}/onnx/test_python/test_zoo_models.py
 
       - name: OVC Python API Tests
-        if: fromJSON(needs.smart_ci.outputs.affected_components).MO.test
+        if: fromJSON(needs.smart_ci.outputs.affected_components).OVC.test
         shell: cmd
         run: |
           :: Used for 'test_utils' installed in '<test_package>\python\openvino\test_utils'
@@ -377,7 +377,7 @@ jobs:
           python3 -m pytest ${{ env.LAYER_TESTS_INSTALL_DIR }}/py_frontend_tests --junitxml=${{ env.INSTALL_TEST_DIR }}/TEST-test_py_fontend.xml
 
       - name: OVC unit tests
-        if: fromJSON(needs.smart_ci.outputs.affected_components).MO.test
+        if: fromJSON(needs.smart_ci.outputs.affected_components).OVC.test
         shell: cmd
         run: python3 -m pytest -s ${{ env.INSTALL_TEST_DIR }}/ovc/unit_tests --junitxml=${{ env.INSTALL_TEST_DIR }}/TEST-OpenVinoConversion.xml
 

.gitignore

@@ -60,17 +60,6 @@ coverage
 .npm
 
 # Artifacts
-/tools/mo/*.bin
-/tools/mo/*.xml
-/tools/mo/*.json
-/tools/mo/*.so
-/tools/mo/*.txt
-/tools/mo/*.pb
-/tools/mo/*.pbtxt
-/tools/mo/!CMakeLists.txt
-/tools/mo/*.mapping
-/tools/mo/*.dat
-/tools/mo/*.svg
 /src/plugins/intel_cpu/tools/commit_slider/*.json
 /src/plugins/intel_cpu/tools/commit_slider/slider_cache/*
 /src/plugins/intel_cpu/thirdparty/ComputeLibrary/build/*

.gitmodules

@@ -52,9 +52,6 @@
 [submodule "thirdparty/onednn_gpu"]
 	path = src/plugins/intel_gpu/thirdparty/onednn_gpu
 	url = https://github.com/oneapi-src/oneDNN.git
-[submodule "tools/pot/thirdparty/open_model_zoo"]
-	path = thirdparty/open_model_zoo
-	url = https://github.com/openvinotoolkit/open_model_zoo.git
 [submodule "thirdparty/json/nlohmann_json"]
 	path = thirdparty/json/nlohmann_json
 	url = https://github.com/nlohmann/json.git

README.md

@@ -1,6 +1,14 @@
 <div align="center">
 <img src="docs/dev/assets/openvino-logo-purple-black.svg" width="400px">
 
+<h3 align="center">
+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>
+</p>
+
 [![PyPI Status](https://badge.fury.io/py/openvino.svg)](https://badge.fury.io/py/openvino)
 [![Anaconda Status](https://anaconda.org/conda-forge/openvino/badges/version.svg)](https://anaconda.org/conda-forge/openvino)
 [![brew Status](https://img.shields.io/homebrew/v/openvino)](https://formulae.brew.sh/formula/openvino)
@@ -10,14 +18,14 @@
 [![brew Downloads](https://img.shields.io/homebrew/installs/dy/openvino)](https://formulae.brew.sh/formula/openvino)
  </div>
 
-Welcome to OpenVINO™, an open-source software toolkit for optimizing and deploying deep learning models.
 
 - **Inference Optimization**: Boost deep learning performance in computer vision, automatic speech recognition, generative AI, natural language processing with large and small language models, and many other common tasks.
-- **Flexible Model Support**: Use models trained with popular frameworks such as TensorFlow, PyTorch, ONNX, Keras, and PaddlePaddle. Convert and deploy models without original frameworks.
+- **Flexible Model Support**: Use models trained with popular frameworks such as PyTorch, TensorFlow, ONNX, Keras, PaddlePaddle, and JAX/Flax. Directly integrate models built with transformers and diffusers from the Hugging Face Hub using Optimum Intel. Convert and deploy models without original frameworks.
 - **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) for a quick reference.
+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.
+
 
 ## Installation
 
@@ -40,6 +48,8 @@ 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).
+
 Here are easy-to-follow code examples demonstrating how to run PyTorch and TensorFlow model inference using OpenVINO:
 
 **PyTorch Model**
@@ -86,25 +96,43 @@ data = np.random.rand(1, 224, 224, 3)
 output = compiled_model({0: data})
 ```
 
-OpenVINO also supports CPU, GPU, and NPU devices and works with models in TensorFlow, PyTorch, ONNX, TensorFlow Lite, PaddlePaddle model formats.
-With OpenVINO you can do automatic performance enhancements at runtime customized to your hardware (preserving model accuracy), including:
-asynchronous execution, batch processing, tensor fusion, load balancing, dynamic inference parallelism, automatic BF16 conversion, and more.
+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.
+
+## 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/learn-openvino/llm_inference_guide/genai-guide.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).
+
+## Documentation
+
+[User documentation](https://docs.openvino.ai/) contains detailed information about OpenVINO and guides you from installation through optimizing and deploying models for your AI applications.
+
+[Developer documentation](./docs/dev/index.md) focuses on the OpenVINO architecture and describes [building](./docs/dev/build.md)  and [contributing](./CONTRIBUTING.md) processes.
 
 ## OpenVINO Ecosystem
 
--   [🤗Optimum Intel](https://github.com/huggingface/optimum-intel) -  a simple interface to optimize Transformers and Diffusers models.
+### OpenVINO Tools
+
 -   [Neural Network Compression Framework (NNCF)](https://github.com/openvinotoolkit/nncf) - advanced model optimization techniques including quantization, filter pruning, binarization, and sparsity.
 -   [GenAI Repository](https://github.com/openvinotoolkit/openvino.genai) and [OpenVINO Tokenizers](https://github.com/openvinotoolkit/openvino_tokenizers) - resources and tools for developing and optimizing Generative AI applications.
 -   [OpenVINO™ Model Server (OVMS)](https://github.com/openvinotoolkit/model_server) - a scalable, high-performance solution for serving models optimized for Intel architectures.
 -   [Intel® Geti™](https://geti.intel.com/) - an interactive video and image annotation tool for computer vision use cases.
 
-Check out the [Awesome OpenVINO](https://github.com/openvinotoolkit/awesome-openvino) repository to discover a collection of community-made AI projects based on OpenVINO!
+### Integrations
 
-## Documentation
+-   [🤗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.
+-   [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.
+-   [LangChain](https://python.langchain.com/docs/integrations/llms/openvino/) - integrate OpenVINO with the LangChain framework to enhance runtime performance for GenAI applications.
 
-[User documentation](https://docs.openvino.ai/) contains detailed information about OpenVINO and guides you from installation through optimizing and deploying models for your AI applications.
+Check out the [Awesome OpenVINO](https://github.com/openvinotoolkit/awesome-openvino) repository to discover a collection of community-made AI projects based on OpenVINO!
 
-[Developer documentation](./docs/dev/index.md) focuses on how OpenVINO [components](./docs/dev/index.md#openvino-components) work and describes [building](./docs/dev/build.md)  and [contributing](./CONTRIBUTING.md) processes.
+## 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.
 
 ## Contribution and Support
 
@@ -118,9 +146,8 @@ You can ask questions and get support on:
 * The [`openvino`](https://stackoverflow.com/questions/tagged/openvino) tag on Stack Overflow\*.
 
 
-## Additional Resources
+## Resources
 
-* [Product Page](https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit.html)
 * [Release Notes](https://docs.openvino.ai/2024/about-openvino/release-notes-openvino.html)
 * [OpenVINO Blog](https://blog.openvino.ai/)
 * [OpenVINO™ toolkit on Medium](https://medium.com/@openvino)
@@ -145,4 +172,3 @@ By contributing to the project, you agree to the license and copyright terms the
 
 ---
 \* Other names and brands may be claimed as the property of others.
-

cmake/dependencies.cmake

@@ -4,7 +4,6 @@
 
 cmake_policy(SET CMP0054 NEW)
 
-# TODO: fix it, outside of source dir MO cannot find TBB dependency
 ov_set_temp_directory(TEMP "${CMAKE_SOURCE_DIR}")
 
 ## Intel OMP package

cmake/developer_package/cross_compile/cross_compiled_func.cmake

@@ -11,7 +11,7 @@ set(_ACCEPTED_ARCHS_AVX     "^(ANY|SSE42|AVX)$")
 set(_ACCEPTED_ARCHS_AVX2    "^(ANY|SSE42|AVX|AVX2)$")
 set(_ACCEPTED_ARCHS_AVX512F "^(ANY|SSE42|AVX|AVX2|AVX512F)$")
 set(_ACCEPTED_ARCHS_NEON_FP16 "^(ANY|NEON_FP16)$")
-set(_ACCEPTED_ARCHS_SVE     "^(ANY|SVE)$")
+set(_ACCEPTED_ARCHS_SVE     "^(ANY|NEON_FP16|SVE)$")
 
 ## Arch specific definitions
 set(_DEFINE_ANY       "")
@@ -186,10 +186,10 @@ endfunction()
 #  Return currently requested ARCH id
 #
 function(_currently_requested_top_arch VAR)
-    if(ENABLE_NEON_FP16)
-        set(RES NEON_FP16)
-    elseif(ENABLE_SVE)
+    if(ENABLE_SVE)
         set(RES SVE)
+    elseif(ENABLE_NEON_FP16)
+        set(RES NEON_FP16)
     elseif(ENABLE_AVX512F)
         set(RES AVX512F)
     elseif(ENABLE_AVX2)

cmake/developer_package/features.cmake

@@ -4,6 +4,7 @@
 
 include(options)
 include(target_flags)
+include(compile_flags/os_flags)
 
 if(WIN32)
     set (CPACK_GENERATOR "ZIP" CACHE STRING "Cpack generator for OpenVINO")
@@ -49,9 +50,9 @@ ov_dependent_option (ENABLE_AVX2 "Enable AVX2 optimizations" ON "X86_64 OR (X86
 
 ov_dependent_option (ENABLE_AVX512F "Enable AVX512 optimizations" ON "X86_64 OR (X86 AND NOT EMSCRIPTEN)" OFF)
 
-ov_dependent_option(ENABLE_NEON_FP16 "Enable ARM FP16 optimizations" ON "AARCH64" OFF)
+ov_dependent_option (ENABLE_NEON_FP16 "Enable ARM FP16 optimizations" ON "AARCH64" OFF)
 
-ov_dependent_option(ENABLE_SVE "Enable SVE optimizations" ON "AARCH64" OFF)
+ov_dependent_option (ENABLE_SVE "Enable SVE optimizations" ON "AARCH64" OFF)
 
 # Type of build, we add this as an explicit option to default it to ON
 get_property(BUILD_SHARED_LIBS_DEFAULT GLOBAL PROPERTY TARGET_SUPPORTS_SHARED_LIBS)
@@ -106,3 +107,11 @@ if(ENABLE_AVX512F)
         set(ENABLE_AVX512F OFF CACHE BOOL "" FORCE)
     endif()
 endif()
+
+if(ENABLE_SVE)
+    ov_check_compiler_supports_sve("-march=armv8-a+sve")
+
+    if(NOT CXX_HAS_SVE)
+        set(ENABLE_SVE OFF CACHE BOOL "" FORCE)
+    endif()
+endif()

docs/articles_en/about-openvino/compatibility-and-support/supported-models.rst

@@ -6,16 +6,14 @@ models from OpenVINO-supported frameworks may also work properly but have not be
 
 **AI Models that run on Intel® Core Ultra™ Processors with OpenVINO™ toolkit:**
 
-.. raw:: html
-
-   <link rel="stylesheet" type="text/css" href="../../_static/css/openVinoDataTables.css">
-
-
-.. csv-table::
+.. data-table:: 
    :class: modeldata stripe
    :name: supportedModelsTable
    :header-rows: 1
    :file:  ../../_static/download/supported_models.csv
+   :data-column-hidden: []
+   :data-order: [[ 0, "asc" ]]
+   :data-page-length: 10
 
 
 | Marked cells indicate models that passed inference with no errors. Empty cells indicate

docs/articles_en/about-openvino/compatibility-and-support/supported-operations.rst

@@ -41,27 +41,36 @@ Data as of OpenVINO 2024.4, 18 Oct. 2024.
 
    .. tab-item:: PyTorch
 
-      .. csv-table::
+      .. data-table::
          :class: modeldata stripe
-         :name: TensorFlow ops
+         :name: TensorFlow_ops_v1
          :header-rows: 1
          :file:  ../../_static/conformance_files/pytorch_ops.csv
+         :data-column-hidden: []
+         :data-order: [[ 0, "asc" ]]
+         :data-page-length: 10
 
    .. tab-item:: TensorFlow
 
-      .. csv-table::
+      .. data-table::
          :class: modeldata stripe
-         :name: TensorFlow ops
+         :name: TensorFlow_ops_v2
          :header-rows: 1
          :file:  ../../_static/conformance_files/tensorflow_ops.csv
+         :data-column-hidden: []
+         :data-order: [[ 0, "asc" ]]
+         :data-page-length: 10
 
    .. tab-item:: PaddlePaddle
 
-      .. csv-table::
+      .. data-table::
          :class: modeldata stripe
-         :name: Paddle ops
+         :name: Paddle_ops
          :header-rows: 1
          :file:  ../../_static/conformance_files/paddlepaddle_ops.csv
+         :data-column-hidden: []
+         :data-order: [[ 0, "asc" ]]
+         :data-page-length: 10
 
    .. tab-item:: ONNX