This get_local_copy() method is only useful for applications which have datasets in the range of < 10gigs and the training machine is the same as dev machine. Most of us(researchers) its not the case, we share GPU time, this is where clearml comes in.
Requirements: The large dataset should only be a single copy preserving the original folder structure which is presumed to be available remotely and the non-mutable access should be provided via dataset_id. This solves everything or atleast most of the thing.