code: def __init__(self, config, random_seed=0):
      super(HyperoptProposer, self).__init__(config)
  
      set_default_keyvalue("engine", "tpe", config, log=logger)
      set_default_keyvalue(
          "random_seed", random_seed, config, log=logger
      )
  
      self.target = (
          -1 if config["target"] == "max" else 1
      )  # default is to minimize
      self.verify_config(config)
      self.nSamples = config["n_samples"]
      self.parameter_config = config["parameter_config"]
      self.space = _convert(self.parameter_config)
      self.rstate = np.random.RandomState(config["random_seed"])
      self.domain = base.Domain(
          lambda x: logger.fatal("should not be run"), self.space
      )
      self.trials = base.Trials()
      self.algo = _get_algo(config["engine"])
  
file_path: auptimizer/src/aup/Proposer/HyperoptProposer.py
imports: import importlib
  import logging
  import numpy
  from six.moves import input
  from .AbstractProposer import AbstractProposer
  from .hyperopt import hp, base
  from .hyperopt.utils import coarse_utcnow
  from ..utils import set_default_keyvalue, check_missing_key, get_from_options
label_desc: Use image node_id 1 to create a new HyperoptProposer object from inherited base classes: AbstractProposer with example: obj = HyperoptProposer(config, random_seed)