class_docstr: An oracle combining random search and greedy algorithm.
  
  It groups the HyperParameters into several categories, namely, HyperGraph,
  Preprocessor, Architecture, and Optimization. The oracle tunes each group
  separately using random search. In each trial, it use a greedy strategy to
  generate new values for one of the categories of HyperParameters and use the
  best trial so far for the rest of the HyperParameters values.
  
  # Arguments
      initial_hps: A list of dictionaries in the form of
          {HyperParameter name (String): HyperParameter value}.
          Each dictionary is one set of HyperParameters, which are used as the
          initial trials for the search. Defaults to None.
      seed: Int. Random seed.
class_docstr_tok: ["An","oracle","combining","random","search","and","greedy","algorithm",".","It","groups","the","HyperParameters","into","several","categories",",","namely",",","HyperGraph",",","Preprocessor",",","Architecture",",","and","Optimization",".","The","oracle","tunes","each","group","separately","using","random","search",".","In","each","trial",",","it","use","a","greedy","strategy","to","generate","new","values","for","one","of","the","categories","of","HyperParameters","and","use","the","best","trial","so","far","for","the","rest","of","the","HyperParameters","values",".","#","Arguments","initial_hps",":","A","list","of","dictionaries","in","the","form","of","{","HyperParameter","name","(","String",")",":","HyperParameter","value","}",".","Each","dictionary","is","one","set","of","HyperParameters",",","which","are","used","as","the","initial","trials","for","the","search",".","Defaults","to","None",".","seed",":","Int",".","Random","seed","."]
code: def _get_best_hps(self):
      best_trials = self.get_best_trials()
      if best_trials:
          return best_trials[0].hyperparameters.copy()
      else:
          return self.hyperparameters.copy()
  
imports: import copy
  from typing import Any
  from typing import Dict
  from typing import List
  from typing import Optional
  import keras_tuner
  import numpy
  from autokeras.engine import tuner
label_desc: Use image node_id 7 for calling the GreedyOracle obj's underlying member method code with example usage: obj._get_best_hps() and returns: best_trials, self