06c9cefed73cfd43f9453c616e1b9d3ef63f58cf,fairseq/models/speech_to_text/s2t_transformer.py,S2TTransformerModel,build_encoder,#Any#Any#,204

Before Change

    @classmethod
    def build_encoder(cls, args):
        encoder = S2TTransformerEncoder(args)
        if getattr(args, "load_pretrained_encoder_from", None):
            encoder = checkpoint_utils.load_pretrained_component_from_model(
                component=encoder, checkpoint=args.load_pretrained_encoder_from
            )

After Change

    @classmethod
    def build_encoder(cls, args):
        encoder = S2TTransformerEncoder(args)
        pretraining_path = getattr(args, "load_pretrained_encoder_from", None)
        if pretraining_path is not None:
            if not Path(pretraining_path).exists():
                logger.warning(
                    f"skipped pretraining because {pretraining_path} does not exist"
                )
            else:
                encoder = checkpoint_utils.load_pretrained_component_from_model(
                    component=encoder, checkpoint=pretraining_path
                )
                logger.info(f"loaded pretrained encoder from: {pretraining_path}")
        return encoder

    @classmethod
    def build_decoder(cls, args, task, embed_tokens):

Instances