o $i @sRddlZddlmZmZddlmZeGdddejZeGdddeZdS)N)AnyDict) PublicAPIc@s<eZdZdZdedeeefdefddZdefddZ d S) StopperaBase class for implementing a Tune experiment stopper. Allows users to implement experiment-level stopping via ``stop_all``. By default, this class does not stop any trials. Subclasses need to implement ``__call__`` and ``stop_all``. Examples: >>> import time >>> from ray import tune >>> from ray.tune import Stopper >>> >>> class TimeStopper(Stopper): ... def __init__(self): ... self._start = time.time() ... self._deadline = 2 # Stop all trials after 2 seconds ... ... def __call__(self, trial_id, result): ... return False ... ... def stop_all(self): ... return time.time() - self._start > self._deadline ... >>> def train_fn(config): ... for i in range(100): ... time.sleep(1) ... tune.report({"iter": i}) ... >>> tuner = tune.Tuner( ... train_fn, ... tune_config=tune.TuneConfig(num_samples=2), ... run_config=tune.RunConfig(stop=TimeStopper()), ... ) >>> print("[ignore]"); result_grid = tuner.fit() # doctest: +ELLIPSIS [ignore]... trial_idresultreturncCt)z@Returns true if the trial should be terminated given the result.NotImplementedErrorselfrrrU/home/ubuntu/veenaModal/venv/lib/python3.10/site-packages/ray/tune/stopper/stopper.py__call__/zStopper.__call__cCr )z4Returns true if the experiment should be terminated.r r rrrstop_all3rzStopper.stop_allN) __name__ __module__ __qualname____doc__strrrboolrrrrrrrs&rc@sJeZdZdZdefddZdedeeefde fdd Z de fd d Z d S) CombinedStopperaCombine several stoppers via 'OR'. Args: *stoppers: Stoppers to be combined. Examples: >>> import numpy as np >>> from ray import tune >>> from ray.tune.stopper import ( ... CombinedStopper, ... MaximumIterationStopper, ... TrialPlateauStopper, ... ) >>> >>> stopper = CombinedStopper( ... MaximumIterationStopper(max_iter=10), ... TrialPlateauStopper(metric="my_metric"), ... ) >>> def train_fn(config): ... for i in range(15): ... tune.report({"my_metric": np.random.normal(0, 1 - i / 15)}) ... >>> tuner = tune.Tuner( ... train_fn, ... run_config=tune.RunConfig(stop=stopper), ... ) >>> print("[ignore]"); result_grid = tuner.fit() # doctest: +ELLIPSIS [ignore]... >>> all(result.metrics["training_iteration"] <= 20 for result in result_grid) True stopperscGs ||_dSN) _stoppers)r rrrr__init__\s zCombinedStopper.__init__rrrcstfdd|jDS)Nc3s|]}|VqdSrr.0srrrr `sz+CombinedStopper.__call__..anyrr rr"rr_szCombinedStopper.__call__cCstdd|jDS)Ncss|]}|VqdSr)rrrrrr#csz+CombinedStopper.stop_all..r$rrrrrbszCombinedStopper.stop_allN) rrrrrrrrrrrrrrrrr8s "r) abctypingrrray.util.annotationsrABCrrrrrrs 0