How to use the hyperactive.HillClimbingOptimizer function in hyperactive

def test_keras_memory():
    from hyperactive import HillClimbingOptimizer

    memory_list = [False, True]
    for memory in memory_list:
        opt = HillClimbingOptimizer(search_config, 1, memory=memory)
        opt.fit(X, y)
        opt.predict(X)
        opt.score(X, y)

def test_keras_scatter_init():
    from hyperactive import HillClimbingOptimizer

    scatter_init_list = [False, 2, 3, 4]
    for scatter_init in scatter_init_list:
        opt = HillClimbingOptimizer(search_config, 1, scatter_init=scatter_init)
        opt.fit(X, y)
        opt.predict(X)
        opt.score(X, y)

def test_HillClimbingOptimizer():
    from hyperactive import HillClimbingOptimizer

    opt0 = HillClimbingOptimizer(
        search_config, n_iter_0, random_state=random_state, verbosity=0, cv=cv, n_jobs=1
    )
    opt0.fit(X, y)

    opt1 = HillClimbingOptimizer(
        search_config,
        n_iter_1,
        random_state=random_state,
        verbosity=0,
        cv=cv,
        n_jobs=n_jobs,
    )
    opt1.fit(X, y)

    assert opt0.score_best < opt1.score_best

def test_keras_scatter_init():
    from hyperactive import HillClimbingOptimizer

    scatter_init_list = [False, 2]
    for scatter_init in scatter_init_list:
        opt = HillClimbingOptimizer(search_config, 1, scatter_init=scatter_init)
        opt.fit(X, y)
        opt.predict(X)
        opt.score(X, y)

def test_keras_cv():
    from hyperactive import HillClimbingOptimizer

    cv_list = [0.1, 0.5, 0.9, 2]
    for cv in cv_list:
        opt = HillClimbingOptimizer(search_config, 1, cv=cv)
        opt.fit(X, y)
        opt.predict(X)
        opt.score(X, y)

def test_keras_n_iter():
    from hyperactive import HillClimbingOptimizer

    n_iter_list = [0, 1, 2]
    for n_iter in n_iter_list:
        opt = HillClimbingOptimizer(search_config, n_iter)
        opt.fit(X, y)
        opt.predict(X)
        opt.score(X, y)

def test_keras_verbosity():
    from hyperactive import HillClimbingOptimizer

    verbosity_list = [0, 1, 2]
    for verbosity in verbosity_list:
        opt = HillClimbingOptimizer(search_config, 1, verbosity=verbosity)
        opt.search(X, y)
        opt.predict(X)
        opt.score(X, y)

def test_keras_memory():
    from hyperactive import HillClimbingOptimizer

    memory_list = [False, True]
    for memory in memory_list:
        opt = HillClimbingOptimizer(search_config, 1, memory=memory)
        opt.search(X, y)
        opt.predict(X)
        opt.score(X, y)

def test_keras():
    from hyperactive import HillClimbingOptimizer

    opt = HillClimbingOptimizer(search_config, 1)
    opt.search(X, y)
    opt.predict(X)
    opt.score(X, y)

def test_keras_cv():
    from hyperactive import HillClimbingOptimizer

    cv_list = [0.1, 0.5, 0.9, 2]
    for cv in cv_list:
        opt = HillClimbingOptimizer(search_config, 1, cv=cv)
        opt.search(X, y)
        opt.predict(X)
        opt.score(X, y)