Dask-Optuna

Dask-Optuna通过利用Optuna现有的分布式优化功能，在Dask集群上并行运行优化实验，从而有助于改善Optuna和Dask之间的集成。它通过提供Dask兼容的 dask_optuna.DaskStorage 存储类来实现，该存储类包装了Optuna存储类（例如Optuna的内存或sqlite存储），可以直接由Optuna使用。例如

import optuna
import joblib
import dask.distributed
import dask_optuna

def objective(trial):
    x = trial.suggest_uniform("x", -10, 10)
    return (x - 2) ** 2

with dask.distributed.Client() as client:
    # Create a study using Dask-compatible storage
    storage = dask_optuna.DaskStorage()
    study = optuna.create_study(storage=storage)
    # Optimize in parallel on your Dask cluster
    with joblib.parallel_backend("dask"):
        study.optimize(objective, n_trials=100, n_jobs=-1)
    print(f"best_params = {study.best_params}")

文档

更多信息，请参阅Dask-Optuna文档

许可协议

MIT许可