ONNX: The Standard for Interoperable Deep Learning Models

The first time I heard about ONNX was during my internship at INRIA. I was working to develop Neural Network Pruning algorithms in the Julia language. There weren't many pre-trained models yet that I could use, so utilizing ONNX to import models developed with other languages and frameworks might have been a solution. In this article, I want to introduce ONNX and explain its enormous potential by also seeing a practical example. ONNX, or Open Neural Network Exchange, is an open-source standard for representing deep learning models. It was developed by Facebook and Microsoft in order to make it easier for researchers and engineers to move models between different deep-learning frameworks and hardware platforms.