Hello all Apache Ignite ML developers: I understand currently Ignite can't save a model after training, in such a way that the model can be re-imported by another Ignite cluster. Correct me if you can save and reload a model but I don't think you can.
Anyway, I'd like to know if you have recommendations on how you can do either one of the following: 1. convert the Ignite model into an interchangeable format? For example there are some emerging standards (such as https://onnx.ai/ for one) and others - have any of you worked with such 2. if not transform the Ignite model into some standard format, how about saving the model into Native persistence, binary serialized format, creating some kind of handle that can shared with other clusters, and then use this to reload the model into a new Ignite session? This question has been asked of me recently, and this would be a good way to let Apache Ignite ML/DL models participate in a broader enterprise model deployment process. -- Sent from: http://apache-ignite-developers.2346864.n4.nabble.com/
