[DOCS] improve legacy section formatting (#23514)
port: https://github.com/openvinotoolkit/openvino/pull/23512
This commit is contained in:
Karol Blaszczak
GitHub
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@ -1,8 +1,8 @@
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.. {#openvino_legacy_features}
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Legacy Features and Components
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==============================
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.. meta::
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:description: A list of deprecated OpenVINO™ components.
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.. toctree::
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:maxdepth: 1
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@ -60,66 +60,66 @@ offering.
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| :doc:`See the Open Model ZOO documentation <legacy-features/model-zoo>`
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| `Check the OMZ GitHub project <https://github.com/openvinotoolkit/open_model_zoo>`__
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| **Apache MXNet, Caffe, and Kaldi model formats**
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| *New solution:* conversion to ONNX via external tools
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| *Old solution:* model support discontinued with OpenVINO 2024.0
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| `The last version supporting Apache MXNet, Caffe, and Kaldi model formats <https://docs.openvino.ai/2023.3/mxnet_caffe_kaldi.html>`__
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| :doc:`See the currently supported frameworks <../openvino-workflow/model-preparation>`
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| **Post-training Optimization Tool (POT)**
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| *New solution:* NNCF extended in OpenVINO 2023.0
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| *Old solution:* POT discontinued with OpenVINO 2024.0
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| Neural Network Compression Framework (NNCF) now offers the same functionality as POT,
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apart from its original feature set.
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Discontinued:
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#############
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| :doc:`See how to use NNCF for model optimization <../openvino-workflow/model-optimization>`
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| `Check the NNCF GitHub project, including documentation <https://github.com/openvinotoolkit/nncf>`__
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.. dropdown:: Apache MXNet, Caffe, and Kaldi model formats
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| **Inference API 1.0**
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| *New solution:* API 2.0 launched in OpenVINO 2022.1
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| *Old solution:* discontinued with OpenVINO 2024.0
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| `The last version supporting API 1.0 <https://docs.openvino.ai/2023.2/openvino_2_0_transition_guide.html>`__
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| *New solution:* conversion to ONNX via external tools
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| *Old solution:* model support discontinued with OpenVINO 2024.0
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| `The last version supporting Apache MXNet, Caffe, and Kaldi model formats <https://docs.openvino.ai/2023.3/mxnet_caffe_kaldi.html>`__
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| :doc:`See the currently supported frameworks <../openvino-workflow/model-preparation>`
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| **Compile tool**
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| *New solution:* the tool is no longer needed
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| *Old solution:* deprecated in OpenVINO 2023.0
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| If you need to compile a model for inference on a specific device, use the following script:
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.. dropdown:: Post-training Optimization Tool (POT)
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.. tab-set::
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| *New solution:* Neural Network Compression Framework (NNCF) now offers the same functionality
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| *Old solution:* POT discontinued with OpenVINO 2024.0
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| :doc:`See how to use NNCF for model optimization <../openvino-workflow/model-optimization>`
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| `Check the NNCF GitHub project, including documentation <https://github.com/openvinotoolkit/nncf>`__
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.. tab-item:: Python
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:sync: py
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.. dropdown:: Inference API 1.0
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.. doxygensnippet:: docs/snippets/export_compiled_model.py
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:language: python
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:fragment: [export_compiled_model]
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| *New solution:* API 2.0 launched in OpenVINO 2022.1
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| *Old solution:* discontinued with OpenVINO 2024.0
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| `The last version supporting API 1.0 <https://docs.openvino.ai/2023.2/openvino_2_0_transition_guide.html>`__
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.. tab-item:: C++
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:sync: cpp
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.. dropdown:: Compile tool
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.. doxygensnippet:: docs/snippets/export_compiled_model.cpp
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:language: cpp
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:fragment: [export_compiled_model]
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| *New solution:* the tool is no longer needed
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| *Old solution:* discontinued with OpenVINO 2023.0
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| If you need to compile a model for inference on a specific device, use the following script:
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.. tab-set::
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| **DL Workbench**
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| *New solution:* DevCloud version
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| *Old solution:* local distribution discontinued in OpenVINO 2022.3
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| The stand-alone version of DL Workbench, a GUI tool for previewing and benchmarking
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deep learning models, has been discontinued. You can use its cloud version:
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| `Intel® Developer Cloud for the Edge <https://www.intel.com/content/www/us/en/developer/tools/devcloud/edge/overview.html>`__.
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.. tab-item:: Python
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:sync: py
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| **OpenVINO™ integration with TensorFlow (OVTF)**
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| *New solution:* Direct model support and OpenVINO Converter (OVC)
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| *Old solution:* discontinued in OpenVINO 2023.0
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| OpenVINO™ Integration with TensorFlow is longer supported, as OpenVINO now features a
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native TensorFlow support, significantly enhancing user experience with no need for
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explicit model conversion.
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.. doxygensnippet:: docs/snippets/export_compiled_model.py
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:language: python
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:fragment: [export_compiled_model]
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.. tab-item:: C++
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:sync: cpp
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.. doxygensnippet:: docs/snippets/export_compiled_model.cpp
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:language: cpp
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:fragment: [export_compiled_model]
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.. dropdown:: DL Workbench
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| *New solution:* DevCloud version
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| *Old solution:* local distribution discontinued in OpenVINO 2022.3
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| The stand-alone version of DL Workbench, a GUI tool for previewing and benchmarking
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deep learning models, has been discontinued. You can use its cloud version:
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| `Intel® Developer Cloud for the Edge <https://www.intel.com/content/www/us/en/developer/tools/devcloud/edge/overview.html>`__.
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.. dropdown:: TensorFlow integration (OVTF)
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| *New solution:* Direct model support and OpenVINO Converter (OVC)
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| *Old solution:* discontinued in OpenVINO 2023.0
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| OpenVINO now features a native TensorFlow support, with no need for explicit model
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conversion.
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@ -27,7 +27,7 @@ OpenVINO supports the following model formats:
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* OpenVINO IR.
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The easiest way to obtain a model is to download it from an online database, such as
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`TensorFlow Hub <https://tfhub.dev/>`__, `Hugging Face <https://huggingface.co/>`__, and
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`Kaggle <https://www.kaggle.com/models>`__, `Hugging Face <https://huggingface.co/>`__, and
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`Torchvision models <https://pytorch.org/hub/>`__. Now you have two options:
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* Skip model conversion and :doc:`run inference <running-inference/integrate-openvino-with-your-application>`
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