code: def run_hyper(
      algo: str,
      model: str,
      dataset: str,
      base_config_file_list: list,
      base_config_dict: dict,
      space: str,
  ):
      hyper_tuning = HyperTuning(
          model=model,
          dataset=dataset,
          base_config_file_list=base_config_file_list,
          base_config_dict=base_config_dict,
          space=space,
          algo=algo,
      )
      hyper_tuning.run()
  
imports: import logging
  import math
  from copy import copy
  from logging import getLogger
  from time import time
  from typing import Optional, Dict, Any, Callable, Union, Iterable, Iterator
  import hyperopt
  import numpy
  from hyperopt import fmin, hp, pyll
  from hyperopt.base import miscs_update_idxs_vals
  from hyperopt.pyll.base import Apply
  from .experiment import Experiment
  from ..utils.dashboard import EpochTracker
label_desc: Use image node_id 1 for calling a global function with example usage: run_hyper(algo, model, dataset, base_config_file_list, base_config_dict, space) without return types