class_docstr: Local Searcher (virtual class to inherit from if you are creating a custom Searcher).
  
  Parameters
  ----------
  search_space: dict
      The configuration space to sample from. It contains the full
      specification of the Hyperparameters with their priors
docstr: Calculates the reward (i.e. validation performance) produced by training under the best configuration identified so far.
  Assumes higher reward values indicate better performance.
docstr_tok: ["Calculates","the","reward","(","i.e",".","validation","performance",")","produced","by","training","under","the","best","configuration","identified","so","far",".","Assumes","higher","reward","values","indicate","better","performance","."]
code: def get_best_reward(self):
      """Calculates the reward (i.e. validation performance) produced by training under the best configuration identified so far.
      Assumes higher reward values indicate better performance.
      """
      if self._results:
          return max(self._results.values())
      return self._reward_while_pending()
  
imports: import logging
  import pickle
  from collections import OrderedDict
  from autogluon.common import space
label_desc: Use image node_id 8 for calling the LocalSearcher obj's underlying member method code with example usage: obj.get_best_reward() and returns: self, max