I’ve written a custom Dataset and a custom RNN model in Pytorch and am wondering how to use it with fastai.
Currently, my dataset returns two dictionaries: X and y
- object id
- meta data
- a time series of categorical data
- a time series of continuous data
y has the labels
My model’s forward function takes 3 variables as input: meta, cat, cont (as contained in X above)
I’m able to create Pytorch dataloaders and run a training loop.
I would like to be able to use the fastai library to train my model. I created a Databunch and tried the one_batch() function. Obviously, some error comes up because we are not expecting dicts but vectors at that point.
My question is: can fastai somehow manage models that have multiple inputs? What would be the best way for me to proceed?