def _optimize_model_to_disc(self,
encoded_data : ApplyDataset,
metadata : Tokenizer,
arg_values : Namespace) \
-> None:
tokenizer = metadata
save_checkpoints(
"apply", metadata, arg_values,
self._optimize_checkpoints(encoded_data, arg_values, tokenizer))
def _optimize_model_to_disc(self,
encoded_data : FeaturesDataset,
metadata : Tuple[Embedding,
List[VecFeature], List[WordFeature]],
arg_values : Namespace) \
-> None:
save_checkpoints(
"features", metadata, arg_values,
self._optimize_checkpoints(encoded_data, arg_values, metadata))
def _optimize_model_to_disc(self,
encoded_data : EncFeaturesDataset,
metadata : Tuple[Tokenizer, Embedding,
List[VecFeature], List[WordFeature]],
arg_values : Namespace) \
-> None:
tokenizer, embedding, vec_features, word_features = metadata
save_checkpoints(
"encfeatures", metadata, arg_values,
self._optimize_checkpoints(encoded_data, arg_values, tokenizer,
embedding))