def accuracy_score(y_true, y_pred, normalize=True, sample_weight=None):
 (y_type, y_true, y_pred) = _check_targets(y_true, y_pred)
 if y_type.startswith('multilabel'):
  differing_labels = count_nonzero((y_true - y_pred), axis=1)
  score = (differing_labels == 0)
 else:
  score = (y_true == y_pred)
 return _weighted_sum(score, sample_weight, normalize)

def accuracy_score ( y_true , y_pred , normalize = True , sample_weight = None ) : ( y_type , y_true , y_pred ) = _check_targets ( y_true , y_pred ) if y_type . startswith ( 'multilabel' ) : differing_labels = count_nonzero ( ( y_true - y_pred ) , axis = 1 ) score = ( differing_labels == 0 ) else : score = ( y_true == y_pred ) return _weighted_sum ( score , sample_weight , normalize )
accuracy classification score .