import numpy as np
from sklearn.metrics import mean_absolute_error as skmean_absolute_error

def mean_absolute_error(y_true, y_pred):
    return np.mean(np.abs(y_true - y_pred))

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