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"""Hyperparameter optimization functionality for backends"""
import abc
import hyperopt
from .backend import AnnifBackend
class HyperparameterOptimizer:
"""Base class for hyperparameter optimizers"""
def __init__(self, backend, corpus):
self._backend = backend
self._corpus = corpus
@abc.abstractmethod
def get_hp_space(self):
"""Get the hyperparameter space definition of this backend"""
pass # pragma: no cover
def _prepare(self):
"""Prepare the optimizer for hyperparameter evaluation"""
def _test(self, hps):
"""Evaluate a set of hyperparameters"""
def optimize(self, n_trials):
"""Find the optimal hyperparameters by testing up to the given number of
hyperparameter combinations"""
self._prepare()
space = self.get_hp_space()
trials = hyperopt.Trials()
best = hyperopt.fmin(
show_progressbar=False,
fn=self._test,
space=space,
algo=hyperopt.tpe.suggest,
max_evals=n_trials,
trials=trials)
return (best, 1 - trials.best_trial['result']['loss'])
class AnnifHyperoptBackend(AnnifBackend):
"""Base class for Annif backends that can perform hyperparameter
optimization"""
def get_hp_optimizer(self, corpus):
"""Get a HyperparameterOptimizer object that can look for
optimal hyperparameter combinations for the given corpus"""
NatLibFi /
Annif
