I’ve been playing around with the 5.3 release version and I think you are correct and this is a bug. I think when you call ImitationTrainer->RunTraining with ReinitPolicy=True it accidentally gets the default policy back instead of the appropriate sized one.
You may be able to work around this by making a dummy network with the RL Trainer, like setup RL, Reinit = true, and then stop training right away. Then in the imitation trainer, you can use that network with Reinit = false. I seemed to have gotten an uncaught editor crash trying this (which is very unfortunate), but I hacked it together really quickly so I may have messed something up.
I can look at the source code from the 5.3 release and send you instructions on how to patch this if you are interested, otherwise this is already somewhat fixed on UE Main branch but that’s because we reworked the python interop.
My intention is to work on the imitation learning tutorial for the driving demo next week, so I may have more info once I get that setup properly.