de102585cb9abb004002559fa865e4d011e1eea9,autosklearn/evaluation/__init__.py,ExecuteTaFuncWithQueue,run,#ExecuteTaFuncWithQueue#Any#Any#Any#Any#Any#,117

Before Change

        if instance_specific is None or instance_specific == "0":
            instance_specific = {}
        else:
            instance_specific = [specific.split("=") for specific in instance_specific.split(",")]
            instance_specific = {specific[0]: specific[1] for specific in instance_specific}
        subsample = instance_specific.get("subsample")
        subsample = int(subsample) if subsample is not None else None

After Change

        D = self.backend.load_datamanager()
        queue = multiprocessing.Queue()

        if not (instance_specific is None or instance_specific == "0"):
            raise ValueError(instance_specific)

        arguments = dict(logger=logging.getLogger("pynisher"),
                         wall_time_in_s=cutoff,
                         mem_in_mb=self.memory_limit)
        obj_kwargs = dict(queue=queue,

Instances