Class or Function Names PFNs4BOSampler Installation pip install -r https://hub.optuna.org/samplers/pfns4bo/requirements.txt Example from __future__ import annotations import os import optuna import optunahub module = optunahub.load_module("samplers/pfns4bo") PFNs4BOSampler = module.PFNs4BOSampler def objective(trial: optuna.Trial) -> float: x = trial.suggest_float("x", -10, 10) return (x - 2) ** 2 if __name__ == "__main__": study = optuna.create_study( sampler=PFNs4BOSampler(), ) study.optimize(objective, n_trials=100) print(study.best_params) print(study.best_value) See example.py for a full example. You need GPU to run this example.
The following figures are experimental results of the comparison between PFNs4BO and the random search.