def cross_val_score(estimator, X, y=None, groups=None, scoring=None, cv=None,
                    n_jobs=1, verbose=0, fit_params=None,
                    pre_dispatch='2*n_jobs'):

   # To ensure multimetric format is not supported
    scorer = check_scoring(estimator, scoring=scoring)

    cv_results = cross_validate(estimator=estimator, X=X, y=y, groups=groups,
                                scoring={'score': scorer}, cv=cv,
                                return_train_score=False,
                                n_jobs=n_jobs, verbose=verbose,
                                fit_params=fit_params,
                                pre_dispatch=pre_dispatch)
    return cv_results['test_score']

from sklearn.model_selection import cross_val_score
from sklearn.linear_model import LogisticRegression
from sklearn.datasets import load_breast_cancer

X, y = load_breast_cancer(return_X_y=True)
lr = LogisticRegression()

cross_val_score(lr, X, y, scoring=['accuracy', 'f1'])

>>> cross_val_score(lr, X, y, scoring=['accuracy', 'f1'])
{'fit_time': array([0.00580502, 0.00351   , 0.00399804]), 'score_time': array([0.00100303, 0.00081301, 0.00084615]), 'test_accuracy': array([0.93684211, 0.96842105, 0.94179894]), 'test_f1': array([0.95081967, 0.97520661, 0.9527897 ])}

>>> cross_val_score(lr, X, y, scoring=['accuracy', 'f1'])
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/mingli/GitHub/personal/scikit-learn/sklearn/model_selection/_validation.py", line 349, in cross_val_score
    scorer = check_scoring(estimator, scoring=scoring)
  File "/Users/mingli/GitHub/personal/scikit-learn/sklearn/metrics/scorer.py", line 305, in check_scoring
    " None. %r was passed" % scoring)
ValueError: scoring value should either be a callable, string or None. ['accuracy', 'f1'] was passed