import numpy as np
from sklearn.metrics import r2_score as skr2_score

def r2_score(y_true, y_pred):
    numerator = np.sum((y_true - y_pred) ** 2)
    denominator = np.sum((y_true - np.mean(y_true)) ** 2)
    return 1 - numerator / denominator

for i in range(10):
    rng = np.random.RandomState(i)
    y_true = rng.rand(10)
    y_pred = rng.rand(10)
    score1 = r2_score(y_true, y_pred)
    score2 = skr2_score(y_true, y_pred)
    assert np.isclose(score1, score2)