Caffe2 models can be easily exported to ONNX format using Python. This enables a vast number of other DL frameworks to use our Caffe2 models for training and inference. The frontend module provided by Caffe2-ONNX does all of the heavy lifting of the exporting. This module is located as the python/onnx/frontend.py file in the Caffe2 source code.
The ch5/export_to_onnx.py script provided along with this book's source code shows how to export an existing Caffe2 model to ONNX format. As an example, consider converting the Caffe2 model of AlexNet that we created in Chapter 4, Working with Caffe. We exported the operators and the weights of this network in Caffe2 to the files predict_net.pb and init_net.pb files respectively.
We can invoke the ONNX conversion script, as follows, to convert this Caffe2 model to an ONNX file named alexnet.onnx:
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