[DOCS] OVC/convert_model Documentation (openvinotoolkit#19555)

* Added OVC and ov.convert_model() description. * Minor corrections. * Small correction. * Include page to toctree. * WIP: Model Preparation * Forked OVC/ov.convert_model documentation sub-directory; reworked model_introduction.md * Reverted ovc-related changes in old MO_DG documentation * State explicitly that MO is considered legacy API * Reduced ovc description in model preparation part; added TF Hub exampe (via file) * Grammar check; removed obsolexte parts not relevant to ovc; better wording * Removed a duplicate of mo-to-ovc transition * Fixed links and some other errors found in documentation build * Resolved XYZ placeholder to the transition guide * Fixed technical issues with links * Up-to-date link to PTQ chapter (instead of obsolete POT) * Fixed strong text ending * Update docs/OV_Converter_UG/prepare_model/convert_model/MO_OVC_transition.md Co-authored-by: Anastasiia Pnevskaia <[email protected]> * Update docs/OV_Converter_UG/prepare_model/convert_model/MO_OVC_transition.md Co-authored-by: Anastasiia Pnevskaia <[email protected]> * Update docs/OV_Converter_UG/prepare_model/convert_model/MO_OVC_transition.md Co-authored-by: Anastasiia Pnevskaia <[email protected]> * Renamed Legacy conversion guides * Fixed links and styles for inlined code * Fixed style for code references * Fixing technical syntax errors in docs * Another attempt to fix docs * Removed all unreferenced images * Better content for Additional Resources in model preporation introduction * MO to OVC transition guide. (#127) * Examples code correction. * Change format of example. * Conflict fix. * Remove wrong change. * Added input_shapes example. * batch example. * Examples format changed. * List item removed. * Remove list for all examples. * Corrected batch example. * Transform example. * Text corrections. * Text correction. * Example correction. * Small correction. * Small correction. * Small correction. * Small correction. * Text corrections. * Links corrected. * Text corrections (#128) * Text corrections. * Example corrected. * Update docs/install_guides/pypi-openvino-dev.md Co-authored-by: Sergey Lyalin <[email protected]> --------- Co-authored-by: Sergey Lyalin <[email protected]> * Many technical fixes, description of recursive flattening of list and tuples * Reorganized structure of Model Conversion toc tree. Removed fp16 dedicated page, merged to Conversion Parameters. * Update docs/OV_Converter_UG/prepare_model/convert_model/Convert_Model_From_TensorFlow.md Co-authored-by: Roman Kazantsev <[email protected]> * Update docs/Documentation/model_introduction.md Co-authored-by: Maciej Smyk <[email protected]> * Fixed example from tf hub. Removed input_shape references * Update docs/Documentation/model_introduction.md Co-authored-by: Tatiana Savina <[email protected]> * Update docs/Documentation/model_introduction.md Co-authored-by: Tatiana Savina <[email protected]> * Update docs/Documentation/model_introduction.md Co-authored-by: Tatiana Savina <[email protected]> * Removed * Update docs/OV_Converter_UG/prepare_model/convert_model/Convert_Model_From_ONNX.md Co-authored-by: Tatiana Savina <[email protected]> * Update docs/OV_Converter_UG/prepare_model/convert_model/Convert_Model_From_ONNX.md Co-authored-by: Tatiana Savina <[email protected]> * Update docs/OV_Converter_UG/prepare_model/convert_model/Convert_Model_From_ONNX.md Co-authored-by: Tatiana Savina <[email protected]> * Update docs/OV_Converter_UG/prepare_model/convert_model/Convert_Model_From_ONNX.md Co-authored-by: Tatiana Savina <[email protected]> * Fixed links * Removed TODO for model flow * Apply suggestions from code review Co-authored-by: Tatiana Savina <[email protected]> * Restored lost code-blocks that leaded to wrong rendering of the code snippets in some places * Apply suggestions from code review Co-authored-by: Tatiana Savina <[email protected]> * Update docs/Documentation/model_introduction.md * Fixed links to notebooks * Apply suggestions from code review Co-authored-by: Tatiana Savina <[email protected]> --------- Co-authored-by: Anastasiia Pnevskaia <[email protected]> Co-authored-by: Karol Blaszczak <[email protected]> Co-authored-by: Roman Kazantsev <[email protected]> Co-authored-by: Maciej Smyk <[email protected]> Co-authored-by: Tatiana Savina <[email protected]>
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diff --git a/docs/Documentation/model_introduction.md b/docs/Documentation/model_introduction.md
diff --git a/docs/MO_DG/Deep_Learning_Model_Optimizer_DevGuide.md b/docs/MO_DG/Deep_Learning_Model_Optimizer_DevGuide.md
@@ -1,4 +1,4 @@
-# Convert a Model {#openvino_docs_MO_DG_Deep_Learning_Model_Optimizer_DevGuide}
+# Legacy Conversion API {#openvino_docs_MO_DG_Deep_Learning_Model_Optimizer_DevGuide}
 
 @sphinxdirective
 
@@ -14,12 +14,15 @@
    openvino_docs_MO_DG_FP16_Compression
    openvino_docs_MO_DG_Python_API
    openvino_docs_MO_DG_prepare_model_Model_Optimizer_FAQ
+   Supported_Model_Formats_MO_DG
 
 .. meta::
-   :description: Model conversion (MO) furthers the transition between training and 
-                 deployment environments, it adjusts deep learning models for 
+   :description: Model conversion (MO) furthers the transition between training and
+                 deployment environments, it adjusts deep learning models for
                  optimal execution on target devices.
 
+.. note::
+   This part of the documentation describes a legacy approach to model conversion. Starting with OpenVINO 2023.1, a simpler alternative API for model conversion is available: ``openvino.convert_model`` and OpenVINO Model Converter ``ovc`` CLI tool. Refer to `Model preparation <openvino_docs_model_processing_introduction>` for more details. If you are still using `openvino.tools.mo.convert_model` or `mo` CLI tool, you can still refer to this documentation. However, consider checking the `transition guide <openvino_docs_OV_Converter_UG_prepare_model_convert_model_MO_OVC_transition>` to learn how to migrate from the legacy conversion API to the new one. Depending on the model topology, the new API can be a better option for you.
 
 To convert a model to OpenVINO model format (``ov.Model``), you can use the following command:
 

diff --git a/docs/MO_DG/prepare_model/FP16_Compression.md b/docs/MO_DG/prepare_model/FP16_Compression.md
@@ -3,7 +3,7 @@
 @sphinxdirective
 
 By default, when IR is saved all relevant floating-point weights are compressed to ``FP16`` data type during model conversion.
-It results in creating a "compressed ``FP16`` model", which occupies about half of 
+It results in creating a "compressed ``FP16`` model", which occupies about half of
 the original space in the file system. The compression may introduce a minor drop in accuracy,
 but it is negligible for most models.
 In case if accuracy drop is significant user can disable compression explicitly.
@@ -29,20 +29,20 @@ To disable compression, use the ``compress_to_fp16=False`` option:
           mo --input_model INPUT_MODEL --compress_to_fp16=False
 
 
-For details on how plugins handle compressed ``FP16`` models, see 
+For details on how plugins handle compressed ``FP16`` models, see
 :doc:`Working with devices <openvino_docs_OV_UG_Working_with_devices>`.
 
 .. note::
 
-   ``FP16`` compression is sometimes used as the initial step for ``INT8`` quantization. 
-   Refer to the :doc:`Post-training optimization <pot_introduction>` guide for more 
+   ``FP16`` compression is sometimes used as the initial step for ``INT8`` quantization.
+   Refer to the :doc:`Post-training optimization <ptq_introduction>` guide for more
    information about that.
 
 
 .. note::
 
    Some large models (larger than a few GB) when compressed to ``FP16`` may consume an overly large amount of RAM on the loading
-   phase of the inference. If that is the case for your model, try to convert it without compression: 
+   phase of the inference. If that is the case for your model, try to convert it without compression:
    ``convert_model(INPUT_MODEL, compress_to_fp16=False)`` or ``convert_model(INPUT_MODEL)``
 
 

diff --git a/docs/MO_DG/prepare_model/convert_model/supported_model_formats.md b/docs/MO_DG/prepare_model/convert_model/supported_model_formats.md
@@ -1,4 +1,4 @@
-# Supported Model Formats {#Supported_Model_Formats}
+# Supported Model Formats {#Supported_Model_Formats_MO_DG}
 
 @sphinxdirective
 
@@ -17,7 +17,7 @@
    :description: Learn about supported model formats and the methods used to convert, read, and compile them in OpenVINO™.
 
 
-**OpenVINO IR (Intermediate Representation)** - the proprietary and default format of OpenVINO, benefiting from the full extent of its features. All other supported model formats, as listed below, are converted to :doc:`OpenVINO IR <openvino_ir>` to enable inference. Consider storing your model in this format to minimize first-inference latency, perform model optimization, and, in some cases, save space on your drive. 
+**OpenVINO IR (Intermediate Representation)** - the proprietary and default format of OpenVINO, benefiting from the full extent of its features. All other supported model formats, as listed below, are converted to :doc:`OpenVINO IR <openvino_ir>` to enable inference. Consider storing your model in this format to minimize first-inference latency, perform model optimization, and, in some cases, save space on your drive.
 
 **PyTorch, TensorFlow, ONNX, and PaddlePaddle** - can be used with OpenVINO Runtime API directly, 
 which means you do not need to save them as OpenVINO IR before including them in your application.
@@ -62,9 +62,9 @@ Here are code examples of how to use these methods with different model formats:
                  ov_model = convert_model(model)
                  compiled_model = core.compile_model(ov_model, "AUTO")
 
-              For more details on conversion, refer to the 
-              :doc:`guide <openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_PyTorch>` 
-              and an example `tutorial <https://docs.openvino.ai/nightly/notebooks/102-pytorch-onnx-to-openvino-with-output.html>`__ 
+              For more details on conversion, refer to the
+              :doc:`guide <openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_PyTorch>`
+              and an example `tutorial <https://docs.openvino.ai/nightly/notebooks/102-pytorch-onnx-to-openvino-with-output.html>`__
               on this topic.
 
    .. tab-item:: TensorFlow
@@ -104,10 +104,10 @@ Here are code examples of how to use these methods with different model formats:
                  ov_model = convert_model("saved_model.pb")
                  compiled_model = core.compile_model(ov_model, "AUTO")
 
-              For more details on conversion, refer to the 
-              :doc:`guide <openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_TensorFlow>` 
-              and an example `tutorial <https://docs.openvino.ai/nightly/notebooks/101-tensorflow-to-openvino-with-output.html>`__ 
-              on this topic. 
+              For more details on conversion, refer to the
+              :doc:`guide <openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_TensorFlow>`
+              and an example `tutorial <https://docs.openvino.ai/nightly/notebooks/101-tensorflow-to-openvino-with-output.html>`__
+              on this topic.
 
             * The ``read_model()`` and ``compile_model()`` methods:
 
@@ -125,8 +125,8 @@ Here are code examples of how to use these methods with different model formats:
                  ov_model = read_model("saved_model.pb")
                  compiled_model = core.compile_model(ov_model, "AUTO")
 
-              For a guide on how to run inference, see how to 
-              :doc:`Integrate OpenVINO™ with Your Application <openvino_docs_OV_UG_Integrate_OV_with_your_application>`. 
+              For a guide on how to run inference, see how to
+              :doc:`Integrate OpenVINO™ with Your Application <openvino_docs_OV_UG_Integrate_OV_with_your_application>`.
               For TensorFlow format, see :doc:`TensorFlow Frontend Capabilities and Limitations <openvino_docs_MO_DG_TensorFlow_Frontend>`.
 
          .. tab-item:: C++
@@ -146,7 +146,7 @@ Here are code examples of how to use these methods with different model formats:
 
                  ov::CompiledModel compiled_model = core.compile_model("saved_model.pb", "AUTO");
 
-              For a guide on how to run inference, see how to 
+              For a guide on how to run inference, see how to
               :doc:`Integrate OpenVINO™ with Your Application <openvino_docs_OV_UG_Integrate_OV_with_your_application>`.
 
          .. tab-item:: C
@@ -167,7 +167,7 @@ Here are code examples of how to use these methods with different model formats:
                  ov_compiled_model_t* compiled_model = NULL;
                  ov_core_compile_model_from_file(core, "saved_model.pb", "AUTO", 0, &compiled_model);
 
-              For a guide on how to run inference, see how to 
+              For a guide on how to run inference, see how to
               :doc:`Integrate OpenVINO™ with Your Application <openvino_docs_OV_UG_Integrate_OV_with_your_application>`.
 
          .. tab-item:: CLI
@@ -206,9 +206,9 @@ Here are code examples of how to use these methods with different model formats:
                  ov_model = convert_model("<INPUT_MODEL>.tflite")
                  compiled_model = core.compile_model(ov_model, "AUTO")
 
-              For more details on conversion, refer to the 
-              :doc:`guide <openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_TensorFlow>` 
-              and an example `tutorial <https://docs.openvino.ai/nightly/notebooks/119-tflite-to-openvino-with-output.html>`__ 
+              For more details on conversion, refer to the
+              :doc:`guide <openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_TensorFlow>`
+              and an example `tutorial <https://docs.openvino.ai/nightly/notebooks/119-tflite-to-openvino-with-output.html>`__
               on this topic.
 
 
@@ -239,7 +239,7 @@ Here are code examples of how to use these methods with different model formats:
 
                  compiled_model = core.compile_model("<INPUT_MODEL>.tflite", "AUTO")
 
-              For a guide on how to run inference, see how to 
+              For a guide on how to run inference, see how to
               :doc:`Integrate OpenVINO™ with Your Application <openvino_docs_OV_UG_Integrate_OV_with_your_application>`.
 
 
@@ -258,7 +258,7 @@ Here are code examples of how to use these methods with different model formats:
 
                  ov::CompiledModel compiled_model = core.compile_model("<INPUT_MODEL>.tflite", "AUTO");
 
-              For a guide on how to run inference, see how to 
+              For a guide on how to run inference, see how to
               :doc:`Integrate OpenVINO™ with Your Application <openvino_docs_OV_UG_Integrate_OV_with_your_application>`.
 
          .. tab-item:: C
@@ -277,7 +277,7 @@ Here are code examples of how to use these methods with different model formats:
                  ov_compiled_model_t* compiled_model = NULL;
                  ov_core_compile_model_from_file(core, "<INPUT_MODEL>.tflite", "AUTO", 0, &compiled_model);
 
-              For a guide on how to run inference, see how to 
+              For a guide on how to run inference, see how to
               :doc:`Integrate OpenVINO™ with Your Application <openvino_docs_OV_UG_Integrate_OV_with_your_application>`.
 
          .. tab-item:: CLI
@@ -297,7 +297,7 @@ Here are code examples of how to use these methods with different model formats:
 
                  mo --input_model <INPUT_MODEL>.tflite
 
-              For details on the conversion, refer to the 
+              For details on the conversion, refer to the
               :doc:`article <openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_TensorFlow_Lite>`.
 
    .. tab-item:: ONNX
@@ -324,9 +324,9 @@ Here are code examples of how to use these methods with different model formats:
                  ov_model = convert_model("<INPUT_MODEL>.onnx")
                  compiled_model = core.compile_model(ov_model, "AUTO")
 
-              For more details on conversion, refer to the 
-              :doc:`guide <openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_ONNX>` 
-              and an example `tutorial <https://docs.openvino.ai/nightly/notebooks/102-pytorch-onnx-to-openvino-with-output.html>`__ 
+              For more details on conversion, refer to the
+              :doc:`guide <openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_ONNX>`
+              and an example `tutorial <https://docs.openvino.ai/nightly/notebooks/102-pytorch-onnx-to-openvino-with-output.html>`__
               on this topic.
 
 
@@ -445,9 +445,9 @@ Here are code examples of how to use these methods with different model formats:
                  ov_model = convert_model("<INPUT_MODEL>.pdmodel")
                  compiled_model = core.compile_model(ov_model, "AUTO")
 
-              For more details on conversion, refer to the 
-              :doc:`guide <openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_Paddle>` 
-              and an example `tutorial <https://docs.openvino.ai/nightly/notebooks/103-paddle-to-openvino-classification-with-output.html>`__ 
+              For more details on conversion, refer to the
+              :doc:`guide <openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_Paddle>`
+              and an example `tutorial <https://docs.openvino.ai/nightly/notebooks/103-paddle-to-openvino-classification-with-output.html>`__
               on this topic.
 
             * The ``read_model()`` method:
@@ -477,7 +477,7 @@ Here are code examples of how to use these methods with different model formats:
 
                  compiled_model = core.compile_model("<INPUT_MODEL>.pdmodel", "AUTO")
 
-              For a guide on how to run inference, see how to 
+              For a guide on how to run inference, see how to
               :doc:`Integrate OpenVINO™ with Your Application <openvino_docs_OV_UG_Integrate_OV_with_your_application>`.
 
          .. tab-item:: C++
@@ -495,7 +495,7 @@ Here are code examples of how to use these methods with different model formats:
 
                  ov::CompiledModel compiled_model = core.compile_model("<INPUT_MODEL>.pdmodel", "AUTO");
 
-              For a guide on how to run inference, see how to 
+              For a guide on how to run inference, see how to
               :doc:`Integrate OpenVINO™ with Your Application <openvino_docs_OV_UG_Integrate_OV_with_your_application>`.
 
          .. tab-item:: C
@@ -514,7 +514,7 @@ Here are code examples of how to use these methods with different model formats:
                  ov_compiled_model_t* compiled_model = NULL;
                  ov_core_compile_model_from_file(core, "<INPUT_MODEL>.pdmodel", "AUTO", 0, &compiled_model);
 
-              For a guide on how to run inference, see how to 
+              For a guide on how to run inference, see how to
               :doc:`Integrate OpenVINO™ with Your Application <openvino_docs_OV_UG_Integrate_OV_with_your_application>`.
 
          .. tab-item:: CLI
@@ -538,8 +538,8 @@ Here are code examples of how to use these methods with different model formats:
               :doc:`article <openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_Paddle>`.
 
 
-**MXNet, Caffe, and Kaldi** are legacy formats that need to be converted explicitly to OpenVINO IR or ONNX before running inference. 
-As OpenVINO is currently proceeding **to deprecate these formats** and **remove their support entirely in the future**, 
+**MXNet, Caffe, and Kaldi** are legacy formats that need to be converted explicitly to OpenVINO IR or ONNX before running inference.
+As OpenVINO is currently proceeding **to deprecate these formats** and **remove their support entirely in the future**,
 converting them to ONNX for use with OpenVINO should be considered the default path.
 
 .. note::