class_docstr: An abstract HPOptimizer using for `advisor` package.
  See https://github.com/tobegit3hub/advisor for more information
  
  Attributes
  ----------
  method : .suggestion.AbstractSuggestionAlgorithm
      The algorithm class in `suggestion`
  max_evals : int
      The max rounds of evaluating HPs
  
  Methods
  -------
  optimize
      Optimize the HP by the method within give model and HP space
class_docstr_tok: ["An","abstract","HPOptimizer","using","for","`","advisor","`","package",".","See","https",":","\/\/github.com\/tobegit3hub\/advisor","for","more","information","Attributes","--","--","--","--","--","method",":",".suggestion.AbstractSuggestionAlgorithm","The","algorithm","class","in","`","suggestion","`","max_evals",":","int","The","max","rounds","of","evaluating","HPs","Methods","--","--","--","-","optimize","Optimize","the","HP","by","the","method","within","give","model","and","HP","space"]
docstr: See .base.BaseHPOptimizer._set_up
docstr_tok: ["See",".base.BaseHPOptimizer._set_up"]
code: def _set_up(self, trainer, dataset, slaves, time_limit, memory_limit):
      """
      See .base.BaseHPOptimizer._set_up
      """
      self.trials = []
      self.new_trials = []
      self.xs = []
      self.best_id = None
      self.best_trainer = None
      space = (
          trainer.hyper_parameter_space
          + trainer.get_model().hyper_parameter_space
      )
      current_config = self._encode_para(space)
  
      for i in range(slaves):
          self.new_trials.append(None)
          self.xs.append(None)
  
      study_configuration_json = {
          "goal": "MINIMIZE",
          "maxTrials": 5,
          "maxParallelTrials": 1,
          "randomInitTrials": 1,
          "params": current_config,
      }
      study_configuration = json.dumps(study_configuration_json)
      self.study = Study.create("HPO", study_configuration)
      self.config = study_configuration_json
  
file_path: AutoGL/autogl/module/hpo/advisorbase.py
imports: import time
  import json
  import math
  from tqdm import trange
  from .suggestion.models import Study
  from .base import BaseHPOptimizer, TimeTooLimitedError
  from .suggestion.algorithm.random_search import RandomSearchAlgorithm
  from .suggestion.algorithm.mocmaes import MocmaesAlgorithm
label_desc: Use image node_id 2 for calling the AdvisorBaseHPOptimizer obj's underlying member method code with example usage: obj._set_up(trainer, dataset, slaves, time_limit, memory_limit) without return types