@robertl seemed to imply in this thread that when training is completed, perceptilabs tries to delete checkpoint files (presumably before writing a new one, but even with this approach it would be nicer if it wrote the new one first, and only deleted the old one after a new file had been written successfully)
OK, it’s not saving checkpoints after training for me so maybe my info is incomplete, but currently a sample checkpoint folder contains only “checkpoint_model.json”
If the checkpoint is a .json then I don’t see how that code deletes it… and currently the only example named checkpoint I have is indeed a json file ‘checkpoint_model.json’. Can you clarify?
(Especially - what could OP’s system have found to delete? Training checkpoint files not json? Implying some checkpoints (e.g. model) are json and others aren’t (e.g. training) - that would be confusing.)
Also: even if… it seems like a missed opportunity: why not just add a new timestamped checkpoint file and allow the user to choose which (latest by default) checkpoint is used for other actions that rely on this file - then the user could compare latest vs earlier.