def load_from_checkpoint(checkpoint_file, corpus, optimizer=SGD): checkpoint = LanguageModel.load_checkpoint(checkpoint_file) return LanguageModelTrainer( checkpoint['model'], corpus, optimizer, epoch=checkpoint['epoch'], split=checkpoint['split'], loss=checkpoint['loss'], optimizer_state=checkpoint['optimizer_state_dict'])
def load_from_checkpoint( checkpoint_file: Path, corpus: TextCorpus, optimizer: Optimizer = SGD ): checkpoint = LanguageModel.load_checkpoint(checkpoint_file) return LanguageModelTrainer( checkpoint["model"], corpus, optimizer, epoch=checkpoint["epoch"], split=checkpoint["split"], loss=checkpoint["loss"], optimizer_state=checkpoint["optimizer_state_dict"], )
def load_checkpoint(checkpoint_file: Union[str, Path], corpus: TextCorpus, optimizer: Optimizer = SGD): if type(checkpoint_file) is str: checkpoint_file = Path(checkpoint_file) checkpoint = LanguageModel.load_checkpoint(checkpoint_file) return LanguageModelTrainer( checkpoint["model"], corpus, optimizer, epoch=checkpoint["epoch"], split=checkpoint["split"], loss=checkpoint["loss"], optimizer_state=checkpoint["optimizer_state_dict"], )