Onnx support for Julia ML frameworks

question

#1

This seems like it’s becoming a thing. https://onnx.ai/getting-started

Any packages providing support for this?


#2

Mike is working on something similar for deeplearn.js here but I don’t know of any existing work for onnx.


#3

Thanks for the reference. Getting deep networks deployed onto web/mobile/embedded devices is a hard problem. Mostly, due to lack of a common standard. In the past I played around with pmml files and subsequently http://dmg.org/pfa/index.html. But it was too hard for me. Hoping for a smoother experience in the near future.


#4

PFA isn’t fully baked yet, and PMML can be frustrating. I had to extend PMML for it to be really useful, but then it wasn’t a standard anymore. The extension was to communicate cutoff thresholds for deployment.

A lot of it comes down to pre- and post-processing needs, rather than communicating the model itself. If you allow that requirement in, it ends up creating an entire new programming/data manipulation language. We didn’t.

A project I’m working on just dropped using PMML for years, in favor of a proprietary JSON format. The main driver in addition to speed was the need to support the communication of model context and version history for governance reasons.

So the question is still wide open on how to communicate models between systems. Lots of people solve it by staying in one system.


#5

there is a new package, but not sure how mature it is.