    def setup_task(cls, args, **kwargs):
        """Setup the task (e.g., load dictionaries).

        Args:
            args (argparse.Namespace): parsed command-line arguments
        """
        dicts, output_dicts = cls.setup_dictionary(args, **kwargs)

        targets = []
        if str(getattr(args, "next_unit_prediction", "false")).lower() == "true":
            targets.append("next")
        if str(getattr(args, "edge_unit_prediction", "false")).lower() == "true":
            targets.append("edge")
        if str(getattr(args, "duration_prediction", "false")).lower() == "true":
            targets.append("duration")
        if len(targets) == 0:
            # standard language modeling
            targets = ["next"]

        return cls(args, dicts, output_dicts, targets=targets)
Setup the task (e.g., load dictionaries).

Args:
args (argparse.Namespace): parsed command-line arguments
fairseq/tasks/speech_dlm_task.py