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Converting an ONNX Model

Introduction to ONNX

ONNX* is a representation format for deep learning models. ONNX allows AI developers easily transfer models between different frameworks that helps to choose the best combination for them. Today, PyTorch*, Caffe2*, Apache MXNet*, Microsoft Cognitive Toolkit* and other tools are developing ONNX support.

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.

Convert an ONNX* Model

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.

To convert an ONNX* model, run Model Optimizer with the path to the input model .onnx file:

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 on the Converting a Model to Intermediate Representation (IR) page.

Supported ONNX* Layers

Refer to Supported Framework Layers for the list of supported standard layers.

Additional Resources

See the Model Conversion 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

• Convert ONNX* GPT-2 Model

• Convert ONNX* Mask R-CNN Model

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