Umm..I don't think it should actually give the same results, unless I'm wrong here. Because according to the code.

    numerator = ((y_true - y_pred) ** 2).sum(dtype=np.float64, axis=axis)
    denominator = ((y_true - y_true.mean(axis=0)) ** 2).sum(dtype=np.float64, axis=axis)

When I do output_weights = 'uniform', it sums up across all dimensions and does the numerator/denominator. When I do `np.mean(r2_score(..., output_weights=None))`, I'm finding 1 - numerator/denominator across all dimensions, and then averaging it.