class_docstr: Hyper Parameter Searcher. A Tuner-like class.
class_docstr_tok: ["Hyper","Parameter","Searcher",".","A","Tuner-like","class","."]
docstr: Retrive a summary of trials.
  
  :return: A summary of all the trials. Currently the entire study is
      returned to allow more flexibility for further analysis and visualization.
docstr_tok: ["Retrive","a","summary","of","trials",".",":","return",":","A","summary","of","all","the","trials",".","Currently","the","entire","study","is","returned","to","allow","more","flexibility","for","further","analysis","and","visualization","."]
code: def search_summary(self):
      """
      Retrive a summary of trials.
  
      :return: A summary of all the trials. Currently the entire study is
          returned to allow more flexibility for further analysis and visualization.
      """
      return _search_summary(self.study)
  
imports: from typing import Any
  import pytorch_lightning
  import copy
  import math
  from pytorch_lightning.trainer.states import TrainerFn, TrainerStatus
  from bigdl.nano.utils.common import invalidInputError
  from bigdl.nano.automl.hpo.backend import create_hpo_backend, SamplerType
  from .objective import Objective
  from ._helper import ResetCallback, CustomEvaluationLoop
  from bigdl.nano.automl.utils.parallel import run_parallel
  from bigdl.nano.automl.hpo.search import _search_summary, _end_search, _create_study, _validate_args, _prepare_args
label_desc: Use image node_id 6 for calling the HPOSearcher obj's underlying member method code with example usage: obj.search_summary() and returns: _search_summary