def test_dt_training_time(dummy_titanic):
    X_train, y_train, X_test, y_test = dummy_titanic

    # Standardize to use depth = 10
    dt = DecisionTree(depth_limit=10)
    latency_array = np.array([train_with_time(dt, X_train, y_train)[1] for i in range(100)])
    time_p95 = np.quantile(latency_array, 0.95)
    assert time_p95 < 1.0, 'Training time at 95th percentile should be < 1.0 sec'


def test_dt_serving_latency(dummy_titanic):
    X_train, y_train, X_test, y_test = dummy_titanic

    # Standardize to use depth = 10
    dt = DecisionTree(depth_limit=10)
    dt.fit(X_train, y_train)

    latency_array = np.array([predict_with_time(dt, X_test)[1] for i in range(500)])
    latency_p99 = np.quantile(latency_array, 0.99)
    assert latency_p99 < 0.004, 'Serving latency at 99th percentile should be < 0.004 sec'