Can we save the models trained during running RForecastPredictor?

[yuhaod]

I noticed that there is no "estimator" class for r-based models in GluonTS and the training is done during the inference (i.e., the call of "RForecastPredictor").

I am wondering whether GluonTS allows the users to save the trained r-based models, so that the users can directly use the saved r-based models without spending time training models when calling "RForecastPredictor.predict()"

Thank you very much!

[yuhaod]

A similar unanswered question was asked in #1993.

[lostella]

@yuhaod the RForecastPredictor does not contain any "state" other than configuration options, and its behavior will be the same every time you call it: it will invoke the RForecast package to get predictions. Even if RForecast exposes the on-the-fly-trained model parameters (which may be the case, but I'm not sure how -- this would be first thing to verify), it is hard to imagine how these would be stored, since there is one per each time series that you predicted: which model to use the next time around? Should we keep the association between item_id and the models?

[yuhaod]

Thank you very much @lostella for the quick response. Yes, I was thinking to keep the association between item_idand the stored local R models. Furthermore, I tried both ETS and ARIMA. The training is pretty slow compared to the global model like DeepAR and MQCNN. For example, it took around half hour for training ETS on elec and a few hours for ARIMA on elec. Is it normal? Thanks!