(
    idx: int,
    overrides: Sequence[str],
    hydra_context: HydraContext,
    config: DictConfig,
    task_function: TaskFunction,
    singleton_state: Dict[Any, Any],
)
return ret
Calls `run_job` in parallel
Calls `run_job` in parallel
Calls run_job in parallel
def execute_job(
    idx: int,
    overrides: Sequence[str],
    hydra_context: HydraContext,
    config: DictConfig,
    task_function: TaskFunction,
    singleton_state: Dict[Any, Any],
) -> JobReturn:
    """Calls `run_job` in parallel"""
    setup_globals()
    Singleton.set_state(singleton_state)

    sweep_config = hydra_context.config_loader.load_sweep_config(
        config, list(overrides)
    )
    with open_dict(sweep_config):
        sweep_config.hydra.job.id = "{}_{}".format(sweep_config.hydra.job.name, idx)
        sweep_config.hydra.job.num = idx
    HydraConfig.instance().set_config(sweep_config)

    ret = run_job(
        hydra_context=hydra_context,
        config=sweep_config,
        task_function=task_function,
        job_dir_key="hydra.sweep.dir",
        job_subdir_key="hydra.sweep.subdir",
    )

    return ret
def execute_job ( idx : int , overrides : Sequence [ str ] , hydra_context : HydraContext , config : DictConfig , task_function : TaskFunction , singleton_state : Dict [ Any , Any ] , ) -> JobReturn : setup_globals ( ) Singleton . set_state ( singleton_state ) sweep_config = hydra_context . config_loader . load_sweep_config ( config , list ( overrides ) ) with open_dict ( sweep_config ) : sweep_config . hydra . job . id = "{}_{}" . format ( sweep_config . hydra . job . name , idx ) sweep_config . hydra . job . num = idx HydraConfig . instance ( ) . set_config ( sweep_config ) ret = run_job ( hydra_context = hydra_context , config = sweep_config , task_function = task_function , job_dir_key = "hydra.sweep.dir" , job_subdir_key = "hydra.sweep.subdir" , ) return ret