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"],
)
