import numpy as np
from sklearn.metrics import brier_score_loss as skbrier_score_loss

def brier_score_loss(y_true, y_prob):
    return np.mean(np.square(y_true - y_prob))

# binary
for i in range(10):
    rng = np.random.RandomState(i)
    y_true = rng.randint(2, size=10)
    y_prob = rng.random_sample(size=10)
    score1 = brier_score_loss(y_true, y_prob)
    score2 = skbrier_score_loss(y_true, y_prob)
    assert np.isclose(score1, score2)