# flake8: noqa

accuracy = 42

# __keras_hyperopt_start__
from ray import tune
from ray.tune.suggest.hyperopt import HyperOptSearch
import keras


# 1. Wrap a Keras model in an objective function.
def objective(config):
    model = keras.models.Sequential()
    model.add(keras.layers.Dense(784, activation=config["activation"]))
    model.add(keras.layers.Dense(10, activation="softmax"))

    model.compile(loss="binary_crossentropy", optimizer="adam", metrics=["accuracy"])
    # model.fit(...)
    # loss, accuracy = model.evaluate(...)
    return {"accuracy": accuracy}


# 2. Define a search space and initialize the search algorithm.
search_space = {"activation": tune.choice(["relu", "tanh"])}
algo = HyperOptSearch()

# 3. Start a Tune run that maximizes accuracy.
analysis = tune.run(
    objective, search_alg=algo, config=search_space, metric="accuracy", mode="max"
)
# __keras_hyperopt_end__