088f8ebb69e21c7759af44c6d207a266f4a5d175,python/ray/tune/examples/skopt_example.py,,,#,29

Before Change

    // Now run the experiment without known rewards

    algo = SkOptSearch(
        optimizer, ["width", "height"],
        metric="mean_loss",
        mode="min",
        points_to_evaluate=previously_run_params)
    scheduler = AsyncHyperBandScheduler(metric="mean_loss", mode="min")
    tune.run(
        easy_objective,
        name="skopt_exp",

After Change

            "steps": 100,
            "width": tune.uniform(0, 20),
            "height": tune.uniform(-100, 100),
            "activation": tune.choice(["relu", "tanh"])
        }
    }

    // Optional: Pass the parameter space yourself

Instances