from keras_tuner.tuners import Hyperband
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense

def build_model(hp):
    model = Sequential()
    model.add(Dense(units=hp.Int('units', min_value=32, max_value=512, step=32), activation='relu', input_shape=(input_dim,)))
    model.add(Dense(1, activation='sigmoid'))
    model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
    return model

tuner = Hyperband(build_model, objective='val_accuracy', max_epochs=10, factor=3, directory='my_dir', project_name='helloworld')
tuner.search(X_train, y_train, epochs=50, validation_split=0.2)

print("Best Hyperparameters:", tuner.get_best_hyperparameters()[0].values)

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