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| import chainer | |
| import logging | |
| def check_early_stop(trainer, epochs): | |
| """Checks an early stopping trigger and warns the user if it's the case | |
| :param trainer: The trainer used for training | |
| :param epochs: The maximum number of epochs | |
| """ | |
| end_epoch = trainer.updater.get_iterator("main").epoch | |
| if end_epoch < (epochs - 1): | |
| logging.warning( | |
| "Hit early stop at epoch " | |
| + str(end_epoch) | |
| + "\nYou can change the patience or set it to 0 to run all epochs" | |
| ) | |
| def set_early_stop(trainer, args, is_lm=False): | |
| """Sets the early stop trigger given the program arguments | |
| :param trainer: The trainer used for training | |
| :param args: The program arguments | |
| :param is_lm: If the trainer is for a LM (epoch instead of epochs) | |
| """ | |
| patience = args.patience | |
| criterion = args.early_stop_criterion | |
| epochs = args.epoch if is_lm else args.epochs | |
| mode = "max" if "acc" in criterion else "min" | |
| if patience > 0: | |
| trainer.stop_trigger = chainer.training.triggers.EarlyStoppingTrigger( | |
| monitor=criterion, | |
| mode=mode, | |
| patients=patience, | |
| max_trigger=(epochs, "epoch"), | |
| ) | |