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Model-Formats-fix (#13386)

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Standardized Additional Resources section for Supported Model Formats along with fixing some ref links in articles.
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Sebastian Golebiewski 2022-11-02 09:58:49 +01:00 committed by GitHub
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8
docs/MO_DG/prepare_model/convert_model/Convert_Model_From_Caffe.md
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@ -86,11 +86,11 @@ The optional parameters without default values and not specified by the user in
Internally, when you run Model Optimizer, it loads the model, goes through the topology, and tries to find each layer type in a list of known layers. Custom layers are layers that are not included in the list. If your topology contains such kind of layers, Model Optimizer classifies them as custom.
## Supported Caffe Layers
For the list of supported standard layers, refer to the [Supported Framework Layers](../Supported_Frameworks_Layers.md) page.
For the list of supported standard layers, refer to the [Supported Framework Layers](@ref openvino_docs_MO_DG_prepare_model_Supported_Frameworks_Layers) page.
## Frequently Asked Questions (FAQ)
Model Optimizer provides explanatory messages when it is unable to complete conversions due to typographical errors, incorrectly used options, or other issues. A message describes the potential cause of the problem and gives a link to [Model Optimizer FAQ](../Model_Optimizer_FAQ.md) which provides instructions on how to resolve most issues. The FAQ also includes links to relevant sections to help you understand what went wrong.
Model Optimizer provides explanatory messages when it is unable to complete conversions due to typographical errors, incorrectly used options, or other issues. A message describes the potential cause of the problem and gives a link to [Model Optimizer FAQ](@ref openvino_docs_MO_DG_prepare_model_Model_Optimizer_FAQ) which provides instructions on how to resolve most issues. The FAQ also includes links to relevant sections to help you understand what went wrong.
## Summary
@ -100,5 +100,5 @@ In this document, you learned:
* Which Caffe models are supported.
* How to convert a trained Caffe model by using Model Optimizer with both framework-agnostic and Caffe-specific command-line options.
## See Also
[Model Conversion Tutorials](Convert_Model_Tutorials.md)
## Additional Resources
See the [Model Conversion Tutorials](@ref openvino_docs_MO_DG_prepare_model_convert_model_tutorials) page for a set of tutorials providing step-by-step instructions for converting specific Caffe models.

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docs/MO_DG/prepare_model/convert_model/Convert_Model_From_Kaldi.md
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@ -74,7 +74,8 @@ Based on this mapping, link inputs and outputs in your application manually as f
must be copied to `Parameter_0_for_Offset_fastlstm2.r_trunc__2Offset_fastlstm2.r_trunc__2_out`.
## Supported Kaldi Layers
For the list of supported standard layers, refer to the [Supported Framework Layers ](../Supported_Frameworks_Layers.md) page.
For the list of supported standard layers, refer to the [Supported Framework Layers ](@ref openvino_docs_MO_DG_prepare_model_Supported_Frameworks_Layers) page.
## See Also
[Model Conversion Tutorials](Convert_Model_Tutorials.md)
## Additional Resources
See the [Model Conversion Tutorials](@ref openvino_docs_MO_DG_prepare_model_convert_model_tutorials) page for a set of tutorials providing step-by-step instructions for converting specific Kaldi models. Here are some examples:
* [Convert Kaldi ASpIRE Chain Time Delay Neural Network (TDNN) Model](@ref openvino_docs_MO_DG_prepare_model_convert_model_kaldi_specific_Aspire_Tdnn_Model)

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docs/MO_DG/prepare_model/convert_model/Convert_Model_From_MxNet.md
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@ -39,11 +39,11 @@ MXNet-specific parameters:
Internally, when you run Model Optimizer, it loads the model, goes through the topology, and tries to find each layer type in a list of known layers. Custom layers are layers that are not included in the list. If your topology contains such kind of layers, Model Optimizer classifies them as custom.
## Supported MXNet Layers
For the list of supported standard layers, refer to the [Supported Framework Layers](../Supported_Frameworks_Layers.md) page.
For the list of supported standard layers, refer to the [Supported Framework Layers](@ref openvino_docs_MO_DG_prepare_model_Supported_Frameworks_Layers) page.
## Frequently Asked Questions (FAQ)
Model Optimizer provides explanatory messages when it is unable to complete conversions due to typographical errors, incorrectly used options, or other issues. A message describes the potential cause of the problem and gives a link to [Model Optimizer FAQ](../Model_Optimizer_FAQ.md) which provides instructions on how to resolve most issues. The FAQ also includes links to relevant sections to help you understand what went wrong.
Model Optimizer provides explanatory messages when it is unable to complete conversions due to typographical errors, incorrectly used options, or other issues. A message describes the potential cause of the problem and gives a link to [Model Optimizer FAQ](@ref openvino_docs_MO_DG_prepare_model_Model_Optimizer_FAQ) which provides instructions on how to resolve most issues. The FAQ also includes links to relevant sections to help you understand what went wrong.
## Summary
@ -53,5 +53,7 @@ In this document, you learned:
* Which MXNet models are supported.
* How to convert a trained MXNet model by using the Model Optimizer with both framework-agnostic and MXNet-specific command-line options.
## See Also
[Model Conversion Tutorials](Convert_Model_Tutorials.md)
## Additional Resources
See the [Model Conversion Tutorials](@ref openvino_docs_MO_DG_prepare_model_convert_model_tutorials) page for a set of tutorials providing step-by-step instructions for converting specific MXNet models. Here are some examples:
* [Convert MXNet GluonCV Model](@ref openvino_docs_MO_DG_prepare_model_convert_model_mxnet_specific_Convert_GluonCV_Models)
* [Convert MXNet Style Transfer Model](@ref openvino_docs_MO_DG_prepare_model_convert_model_mxnet_specific_Convert_Style_Transfer_From_MXNet)

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docs/MO_DG/prepare_model/convert_model/Convert_Model_From_ONNX.md
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@ -5,7 +5,7 @@
## Converting an ONNX Model <a name="Convert_From_ONNX"></a>
This page provides instructions on how to convert a model from the ONNX format to the OpenVINO IR format using Model Optimizer. To use Model Optimizer, install OpenVINO Development Tools by following the [installation instructions](https://docs.openvino.ai/latest/openvino_docs_install_guides_install_dev_tools.html).
This page provides instructions on how to convert a model from the ONNX format to the OpenVINO IR format using Model Optimizer. To use Model Optimizer, install OpenVINO Development Tools by following the [installation instructions](@ref openvino_docs_install_guides_install_dev_tools).
The Model Optimizer process assumes you have an ONNX model that was directly downloaded from a public repository or converted from any framework that supports exporting to the ONNX format.
@ -15,14 +15,14 @@ To convert an ONNX model, run Model Optimizer with the path to the input model `
mo --input_model <INPUT_MODEL>.onnx
```
There are no ONNX specific parameters, so only framework-agnostic parameters are available to convert your model. For details, see the *General Conversion Parameters* section in the [Converting a Model to Intermediate Representation (IR)](Converting_Model.md) guide.
There are no ONNX specific parameters, so only framework-agnostic parameters are available to convert your model. For details, see the *General Conversion Parameters* section in the [Converting a Model to Intermediate Representation (IR)](@ref openvino_docs_MO_DG_prepare_model_convert_model_Converting_Model) guide.
## Supported ONNX Layers
For the list of supported standard layers, refer to the [Supported Framework Layers](../Supported_Frameworks_Layers.md) page.
For the list of supported standard layers, refer to the [Supported Framework Layers](@ref openvino_docs_MO_DG_prepare_model_Supported_Frameworks_Layers) page.
## Additional Resources
See the [Model Conversion Tutorials](Convert_Model_Tutorials.md) page for a set of tutorials providing step-by-step instructions for converting specific ONNX models. Here are some examples:
* [Convert ONNX* Faster R-CNN Model](onnx_specific/Convert_Faster_RCNN.md)
* [Convert ONNX* GPT-2 Model](onnx_specific/Convert_GPT2.md)
* [Convert ONNX* Mask R-CNN Model](onnx_specific/Convert_Mask_RCNN.md)
See the [Model Conversion Tutorials](@ref openvino_docs_MO_DG_prepare_model_convert_model_tutorials) page for a set of tutorials providing step-by-step instructions for converting specific ONNX models. Here are some examples:
* [Convert ONNX Faster R-CNN Model](@ref openvino_docs_MO_DG_prepare_model_convert_model_onnx_specific_Convert_Faster_RCNN)
* [Convert ONNX GPT-2 Model](@ref openvino_docs_MO_DG_prepare_model_convert_model_onnx_specific_Convert_GPT2)
* [Convert ONNX Mask R-CNN Model](@ref openvino_docs_MO_DG_prepare_model_convert_model_onnx_specific_Convert_Mask_RCNN)

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docs/MO_DG/prepare_model/convert_model/Convert_Model_From_Paddle.md
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@ -12,7 +12,7 @@ To convert a PaddlePaddle model, use the `mo` script and specify the path to the
```
## Supported PaddlePaddle Layers
For the list of supported standard layers, refer to the [Supported Framework Layers](../Supported_Frameworks_Layers.md) page.
For the list of supported standard layers, refer to the [Supported Framework Layers](@ref openvino_docs_MO_DG_prepare_model_Supported_Frameworks_Layers) page.
## Officially Supported PaddlePaddle Models
The following PaddlePaddle models have been officially validated and confirmed to work (as of OpenVINO 2022.1):
@ -70,7 +70,7 @@ The following PaddlePaddle models have been officially validated and confirmed t
@endsphinxdirective
## Frequently Asked Questions (FAQ)
When Model Optimizer is unable to run to completion due to typographical errors, incorrectly used options, or other issues, it provides explanatory messages. They describe the potential cause of the problem and give a link to the [Model Optimizer FAQ](../Model_Optimizer_FAQ.md), which provides instructions on how to resolve most issues. The FAQ also includes links to relevant sections in the Model Optimizer Developer Guide to help you understand what went wrong.
When Model Optimizer is unable to run to completion due to typographical errors, incorrectly used options, or other issues, it provides explanatory messages. They describe the potential cause of the problem and give a link to the [Model Optimizer FAQ](@ref openvino_docs_MO_DG_prepare_model_Model_Optimizer_FAQ), which provides instructions on how to resolve most issues. The FAQ also includes links to relevant sections in the Model Optimizer Developer Guide to help you understand what went wrong.
## See Also
[Model Conversion Tutorials](Convert_Model_Tutorials.md)
## Additional Resources
See the [Model Conversion Tutorials](@ref openvino_docs_MO_DG_prepare_model_convert_model_tutorials) page for a set of tutorials providing step-by-step instructions for converting specific PaddlePaddle models.

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docs/MO_DG/prepare_model/convert_model/Convert_Model_From_PyTorch.md
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@ -3,7 +3,7 @@
The PyTorch framework is supported through export to the ONNX format. In order to optimize and deploy a model that was trained with it:
1. [Export a PyTorch model to ONNX](#export-to-onnx).
2. [Convert the ONNX model](Convert_Model_From_ONNX.md) to produce an optimized [Intermediate Representation](../../IR_and_opsets.md) of the model based on the trained network topology, weights, and biases values.
2. [Convert the ONNX model](Convert_Model_From_ONNX.md) to produce an optimized [Intermediate Representation](@ref openvino_docs_MO_DG_IR_and_opsets) of the model based on the trained network topology, weights, and biases values.
## Exporting a PyTorch Model to ONNX Format <a name="export-to-onnx"></a>
PyTorch models are defined in Python. To export them, use the `torch.onnx.export()` method. The code to
@ -32,5 +32,8 @@ torch.onnx.export(model, (dummy_input, ), 'model.onnx')
It is recommended to export models to opset 11 or higher when export to default opset 9 is not working. In that case, use `opset_version`
option of the `torch.onnx.export`. For more information about ONNX opset, refer to the [Operator Schemas](https://github.com/onnx/onnx/blob/master/docs/Operators.md) page.
## See Also
[Model Conversion Tutorials](Convert_Model_Tutorials.md)
## Additional Resources
See the [Model Conversion Tutorials](@ref openvino_docs_MO_DG_prepare_model_convert_model_tutorials) page for a set of tutorials providing step-by-step instructions for converting specific PyTorch models. Here are some examples:
* [Convert PyTorch BERT-NER Model](@ref openvino_docs_MO_DG_prepare_model_convert_model_pytorch_specific_Convert_Bert_ner)
* [Convert PyTorch RCAN Model](@ref openvino_docs_MO_DG_prepare_model_convert_model_pytorch_specific_Convert_RCAN)
* [Convert PyTorch YOLACT Model](@ref openvino_docs_MO_DG_prepare_model_convert_model_pytorch_specific_Convert_YOLACT)

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docs/MO_DG/prepare_model/convert_model/Convert_Model_From_TensorFlow.md
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@ -2,7 +2,7 @@
This page provides general instructions on how to convert a model from a TensorFlow format to the OpenVINO IR format using Model Optimizer. The instructions are different depending on whether your model was created with TensorFlow v1.X or TensorFlow v2.X.
To use Model Optimizer, install OpenVINO Development Tools by following the [installation instructions](../../../install_guides/installing-model-dev-tools.md).
To use Model Optimizer, install OpenVINO Development Tools by following the [installation instructions](@ref openvino_docs_install_guides_install_dev_tools).
## Converting TensorFlow 1 Models <a name="Convert_From_TF2X"></a>
@ -140,10 +140,10 @@ mo --saved_model_dir BERT --input mask,word_ids,type_ids --input_shape [2,30],[2
```
## Supported TensorFlow and TensorFlow 2 Keras Layers
For the list of supported standard layers, refer to the [Supported Framework Layers ](../Supported_Frameworks_Layers.md) page.
For the list of supported standard layers, refer to the [Supported Framework Layers ](@ref openvino_docs_MO_DG_prepare_model_Supported_Frameworks_Layers) page.
## Frequently Asked Questions (FAQ)
The Model Optimizer provides explanatory messages if it is unable to run to completion due to typographical errors, incorrectly used options, or other issues. The message describes the potential cause of the problem and gives a link to the [Model Optimizer FAQ](../Model_Optimizer_FAQ.md). The FAQ provides instructions on how to resolve most issues. The FAQ also includes links to relevant sections in the Model Optimizer Developer Guide to help you understand what went wrong.
The Model Optimizer provides explanatory messages if it is unable to run to completion due to typographical errors, incorrectly used options, or other issues. The message describes the potential cause of the problem and gives a link to the [Model Optimizer FAQ](@ref openvino_docs_MO_DG_prepare_model_Model_Optimizer_FAQ). The FAQ provides instructions on how to resolve most issues. The FAQ also includes links to relevant sections in the Model Optimizer Developer Guide to help you understand what went wrong.
## Summary
In this document, you learned:
@ -154,8 +154,8 @@ In this document, you learned:
* How to convert a trained TensorFlow model using the Model Optimizer with both framework-agnostic and TensorFlow-specific command-line options.
## Additional Resources
For step-by-step instructions on how to convert specific TensorFlow models, see the [Model Conversion Tutorials](Convert_Model_Tutorials.md) page. Here are some examples:
* [Convert TensorFlow EfficientDet Models](tf_specific/Convert_EfficientDet_Models.md)
* [Convert TensorFlow FaceNet Models](tf_specific/Convert_FaceNet_From_Tensorflow.md)
* [Convert TensorFlow Object Detection API Models](tf_specific/Convert_Object_Detection_API_Models.md)
See the [Model Conversion Tutorials](@ref openvino_docs_MO_DG_prepare_model_convert_model_tutorials) page for a set of tutorials providing step-by-step instructions for converting specific TensorFlow models. Here are some examples:
* [Convert TensorFlow EfficientDet Models](@ref openvino_docs_MO_DG_prepare_model_convert_model_tf_specific_Convert_EfficientDet_Models)
* [Convert TensorFlow FaceNet Models](@ref openvino_docs_MO_DG_prepare_model_convert_model_tf_specific_Convert_FaceNet_From_Tensorflow)
* [Convert TensorFlow Object Detection API Models](@ref openvino_docs_MO_DG_prepare_model_convert_model_tf_specific_Convert_Object_Detection_API_Models)