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))