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krfricke
619e44e54a
Co-authored-by: Richard Liaw <rliaw@berkeley.edu> Co-authored-by: Kai Fricke <kai@anyscale.com>
43 lines
1.1 KiB
Python
43 lines
1.1 KiB
Python
class Trial:
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hypers: dict = {} # static
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config: dict = {} # static
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status: str = None
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trace: List[Dict] = []
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checkpoints: List[str] = []
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space = {}
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trials = []
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trial_checkpoints = {}
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while not Optimizer.is_finished():
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while Optimizer.has_next(space, trials, state):
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trials += [Optimizer.next(space, trials, state)]
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trial = Optimizer.choose(trials, state)
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if Optimizer.should_stop(trial, trials, state):
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Executor.stop(trial)
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elif Optimizer.should_pause(trial, state):
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Executor.pause(trial)
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elif Optimizer.should_restore(trial, state):
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restore(trial, trial.checkpoints[-1])
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elif Optimizer.should_save(trial, state):
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checkpoint = save(trial)
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elif Optimizer.should_continue(trial, state):
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step(trial)
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exp = Experiment(logdir, name, restore=True)
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failed_trials = exp.get_failed_trials()
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run(failed_trials)
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exp = Experiment(logdir, name, restore=True)
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trials = exp.trials_finished()
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trials.reset_status()
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run(trials)
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optimizer = Optimizer(sweep, metric, *parameters)
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sweep.configure_server()
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sweep.add_logger(Logging)
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sweep.set_executor(executor)
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sweep.run(func, verbose=verbose) |