§ &`ƒieãóh—ddlmZmZmZmZmZddlmZerddlm Z eGd„d¦«¦«Z dS)é)Ú TYPE_CHECKINGÚDictÚListÚOptionalÚUnion)Ú DeveloperAPI)Ú Experimentcó$—eZdZdZdZdZed„¦«Zdee dee de de fd „Z ed „¦«Z d ed ed e e e fffd „Zd„Zde de fd„Z dde dee de fd„Zde fd„Zd„Zde de fd„Zde fd„Zde fd„ZdS)ÚSearchAlgorithmaÂInterface 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`. FNcó—|jS)N©Ú_metric©Úselfs út/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/ray/tune/search/search_algorithm.pyÚmetriczSearchAlgorithm.metrics €àŒ|ÐórÚmodeÚconfigÚreturnc ó.—|jr|rdS|r||_dS)ayPass search properties to search algorithm. This method acts as an alternative to instantiating search algorithms with their own specific search spaces. Instead they can accept a Tune config through this method. The search algorithm will usually pass this method to their ``Searcher`` instance. Args: metric: Metric to optimize mode: One of ["min", "max"]. Direction to optimize. config: Tune config dict. **spec: Any kwargs for forward compatiblity. Info like Experiment.PUBLIC_KEYS is provided through here. FTr )rrrrÚspecs rÚset_search_propertiesz%SearchAlgorithm.set_search_propertiess.€ð& Œ<ð ˜Fð Ø5Ø ð "Ø!ˆDŒL؈trcó—dS)z*Get number of total trials to be generatedr©rs rÚ total_sampleszSearchAlgorithm.total_samples8s €ðˆqrÚ experimentsr có—t‚)zqTracks given experiment specifications. Arguments: experiments: Experiments to run. ©ÚNotImplementedError)rrs rÚadd_configurationsz"SearchAlgorithm.add_configurations=s €õ"Ð!rcó—t‚)z„Returns single Trial object to be queued into the TrialRunner. Returns: trial: Returns a Trial object. rrs rÚ next_trialzSearchAlgorithm.next_trialGs €õ "Ð!rÚtrial_idÚresultcó—dS)zõCalled on each intermediate result returned by a trial. This will only be called when the trial is in the RUNNING state. Arguments: trial_id: Identifier for the trial. result: Result dictionary. Nr)rr$r%s rÚon_trial_resultzSearchAlgorithm.on_trial_resultOs €ð ˆrÚerrorcó—dS)aÇNotification 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. Nr)rr$r%r(s rÚon_trial_completez!SearchAlgorithm.on_trial_completeZs €ð ˆrcó—|jS)zŠReturns True if no trials left to be queued into TrialRunner. Can return True before all trials have finished executing. ©Ú _finishedrs rÚ is_finishedzSearchAlgorithm.is_finishedjs €ð Œ~Ðrcó—d|_dS)z'Marks the search algorithm as finished.TNr,rs rÚ set_finishedzSearchAlgorithm.set_finishedqs €àˆŒˆˆrÚdirpathcó—dS)z4Should return False if restoring is not implemented.Fr©rr1s rÚhas_checkpointzSearchAlgorithm.has_checkpointus€àˆurc ó—dS)zSaves a search algorithm.Nr)rr1Úkwargss rÚ save_to_dirzSearchAlgorithm.save_to_diryó€à ˆrcó—dS)z9Restores a search algorithm along with its wrapped state.Nrr3s rÚrestore_from_dirz SearchAlgorithm.restore_from_dir}r8r)NF)Ú__name__Ú __module__Ú __qualname__Ú__doc__r-rÚpropertyrrÚstrrÚboolrrrrr!r#r'r*r.r0r4r7r:rrrr r s¾€€€€€ð ð ð€Ià€Gà ððñ„Xððؘs”mðØ+3°C¬=ðØBFðà ððððð2ððñ„Xðð"Ø  ¨t°LÔ/AÀ4ÈÈTÈ Ä?Ð!RÔSð"ð"ð"ð"ð"ð"ð"ð  ¨ð  °Tð  ð  ð  ð  ðKPð ð Øð Ø%-¨d¤^ð ØCGð ð ð ð ð ˜Tðððððððð cð¨dððððð  3ð ð ð ð ð ¨ð ð ð ð ð ð rr N) ÚtypingrrrrrÚray.util.annotationsrÚray.tune.experimentr r rrrúrEs£ðØ=Ð=Ð=Ð=Ð=Ð=Ð=Ð=Ð=Ð=Ð=Ð=Ð=Ð=à-Ð-Ð-Ð-Ð-Ð-àð/Ø.Ð.Ð.Ð.Ð.Ð.ððu ðu ðu ðu ðu ñu ôu ñ„ðu ðu ðu r