def update_trial_time(study: optuna.study.Study,
trial: optuna.trial.FrozenTrial):
"""Callback for number of iteration with time cut-off.
Args:
study: optuna study object.
trial: optuna trial object.
"""
ml_algo.mean_trial_time = study.trials_dataframe(
)['duration'].mean().total_seconds()
self.estimated_n_trials = min(
self.n_trials, self.timeout // ml_algo.mean_trial_time)
def update_trial_time(study: optuna.study.Study, trial: optuna.trial.FrozenTrial):
"""Callback for number of iteration with time cut-off.
Args:
study: Optuna study object.
trial: Optuna trial object.
"""
ml_algo.mean_trial_time = study.trials_dataframe()["duration"].mean().total_seconds()
self.estimated_n_trials = min(self.n_trials, self.timeout // ml_algo.mean_trial_time)
logger.info3(
f"\x1b[1mTrial {len(study.trials)}\x1b[0m with hyperparameters {trial.params} scored {trial.value} in {trial.duration}"
)
