class_docstr: Interface of an event handler API for hyperparameter search.
  
  Unlike TrialSchedulers, SearchAlgorithms will not have the ability
  to modify the execution (i.e., stop and pause trials).
  
  Trials added manually (i.e., via the Client API) will also notify
  this class upon new events, so custom search algorithms should
  maintain a list of trials ID generated from this class.
  
  See also: `ray.tune.search.BasicVariantGenerator`.
class_docstr_tok: ["Interface","of","an","event","handler","API","for","hyperparameter","search",".","Unlike","TrialSchedulers",",","SearchAlgorithms","will","not","have","the","ability","to","modify","the","execution","(","i.e.",",","stop","and","pause","trials",")",".","Trials","added","manually","(","i.e.",",","via","the","Client","API",")","will","also","notify","this","class","upon","new","events",",","so","custom","search","algorithms","should","maintain","a","list","of","trials","ID","generated","from","this","class",".","See","also",":","`","ray.tune.search.BasicVariantGenerator","`","."]
docstr: Notification for the completion of trial.
  
  Arguments:
      trial_id: Identifier for the trial.
      result: Defaults to None. A dict will
          be provided with this notification when the trial is in
          the RUNNING state AND either completes naturally or
          by manual termination.
      error: Defaults to False. True if the trial is in
          the RUNNING state and errors.
docstr_tok: ["Notification","for","the","completion","of","trial",".","Arguments",":","trial_id",":","Identifier","for","the","trial",".","result",":","Defaults","to","None",".","A","dict","will","be","provided","with","this","notification","when","the","trial","is","in","the","RUNNING","state","AND","either","completes","naturally","or","by","manual","termination",".","error",":","Defaults","to","False",".","True","if","the","trial","is","in","the","RUNNING","state","and","errors","."]
code: def on_trial_complete(
      self,
      trial_id: str,
      result: Optional[Dict] = None,
      error: bool = False,
  ):
      """Notification for the completion of trial.
  
      Arguments:
          trial_id: Identifier for the trial.
          result: Defaults to None. A dict will
              be provided with this notification when the trial is in
              the RUNNING state AND either completes naturally or
              by manual termination.
          error: Defaults to False. True if the trial is in
              the RUNNING state and errors.
      """
      pass
  
file_path: ray/python/ray/tune/search/search_algorithm.py
imports: from typing import Dict, List, Optional, Union, TYPE_CHECKING
  from ray.util.annotations import DeveloperAPI
label_desc: Use image node_id 7 for calling the SearchAlgorithm obj's underlying member method code with example usage: obj.on_trial_complete(trial_id, result, error) without return types