How to use the fancyimpute.MatrixFactorization function in fancyimpute

def test_matrix_factorization_with_low_rank_random_matrix():
    solver = MatrixFactorization(
        learning_rate=0.01,
        rank=3,
        l2_penalty=0,
        min_improvement=1e-6)
    XY_completed = solver.fit_transform(XY_incomplete)
    _, missing_mae = reconstruction_error(
        XY,
        XY_completed,
        missing_mask,
        name="MatrixFactorization")
    assert missing_mae < 0.1, "Error too high!"

def impute_mf(X, mask, hyperparams={'rank':[5,10,50],'l2_penalty':[1e-3, 1e-5]}):
    return fancyimpute_hpo(MatrixFactorization, hyperparams, X, mask)