How automaticly load best model checkpoint on Trainer instance with TestTubeLogger
The only way I've found to resume the training of a model from the best checkpoint is to explicitly instance Trainer with following structure:
best_epoch = 250  ## ?? (Actually i dont know)
self.trainer = ptl.Trainer(
    logger=TestTubeLogger(
        save_dir=self.save_dir,
        version=0  # fixed 
      ),        
    resume_from_checkpoint=str(self.save_dir / 'default' / 'version_0' / 'checkpoints' / 'epoch={}.ckpt'.format(best_epoch)),
    default_root_dir=self.save_dir,                                                                                                                                                                 )
The problem is that is not natural to know the exact epoch which has the better model.
I think loading the best model is a pretty natural operation for most of the cases:
Training: You want to continue training from the best model.
Test: You want to test the best model.
I think a method to find the "best checkpoint" is the kind of boilerplate code this library tries to avoid.