import wandb
from wandb.sweeps.config import tune
from wandb.sweeps.config.tune.suggest.hyperopt import HyperOptSearch
from wandb.sweeps.config.hyperopt import hp
​
tune_config = tune.run(
    "train.py",
    search_alg=HyperOptSearch(
        dict(
            width=hp.uniform("width", 0, 20),
            height=hp.uniform("height", -100, 100),
            activation=hp.choice("activation", ["relu", "tanh"])),
        metric="mean_loss",
        mode="min"),
    num_samples=10)
​
# Save sweep as yaml config file
tune_config.save("sweep-hyperopt.yaml")
​
# Create the sweep
wandb.sweep(tune_config)