`trw.hparams.params_optimizer_hyperband`¶

Module Contents¶

Classes¶

HyperParametersOptimizerHyperband

Implementation of Hyperband: a novel bandit based approach to hyper-parameter optimization 1

Functions¶

log_hyperband(msg)

Attributes¶

logger

trw.hparams.params_optimizer_hyperband.logger¶

trw.hparams.params_optimizer_hyperband.log_hyperband(msg)¶

class trw.hparams.params_optimizer_hyperband.HyperParametersOptimizerHyperband(evaluate_fn: Callable[[trw.hparams.params.HyperParameters, float], Tuple[trw.hparams.store.Metrics, trw.basic_typing.History, Any]], loss_fn: Callable[[trw.hparams.store.Metrics], float], max_iter: int = 81, eta: int = 3, repeat: int = 100, log_string: Callable[[str], None] = log_hyperband, always_include_default_hparams_in_each_cycle: bool = True)¶

Bases: trw.hparams.params_optimizer.HyperParametersOptimizer

Implementation of Hyperband: a novel bandit based approach to hyper-parameter optimization [#]_

1: https://arxiv.org/abs/1603.06560

_repeat_one(self, repeat_id, nb_runs, hyper_parameters: trw.hparams.params.HyperParameters, store: Optional[trw.hparams.store.RunStore] = None) → Tuple[List[trw.hparams.store.RunResult], int]¶

Run full Hyperband search

Parameters

repeat_id – the iteration number
nb_runs – the run number
store – how to store the result
hyper_parameters – the hyper-parameters

Returns

a tuple of list of runs and number of runs for this iteration og hyperband

optimize(self, store: Optional[trw.hparams.store.RunStore], hyper_parameters: Optional[trw.hparams.params.HyperParameters] = None) → List[trw.hparams.store.RunResult]¶

Optimize the hyper parameters using Hyperband