I'm using a single face set (data_src) as input for a lot of different outputs (data_dst).
Therefore, I'd like to pretrain a model on just my input faceset (data_src).

To facilitate this, I've made a faceset pack of my data_src, and copied that over the "Pretrain_celebA" set, and then pretrain using my own set.
This allows me to pretrain with my own dataset with better settings than when I'm doing a "normal" train that also includes a data_dst set as less memory is being used, so I can bump the batch size up to 7 when pretraining.
Once my pretrain using my own dataset is up to acceptable levels, I can copy it to a new model and start doing a "normal" train with both data_src and data_dst, only this time my data_src has already been pretrained / copied so starts out with a big advantage.

I'd love to be able to do "single input" training like this a bit easier, so I can train on ONLY data_src, or ONLY data_dst.
This way I can train partial input models / output models and reuse / mix and match later.

I hope you get what I mean :-)