code: def test_multilabel():
      """Check if error is raised for multilabel classification."""
      X, y = make_multilabel_classification(
          n_classes=2,
          n_labels=1,
          allow_unlabeled=False,
          random_state=123,
      )
      clf = OneVsRestClassifier(SVC(kernel="linear"))
  
      eclf = VotingClassifier(estimators=[("ovr", clf)], voting="hard")
  
      try:
          eclf.fit(X, y)
      except NotImplementedError:
          return
  
imports: import re
  import numpy
  import pytest
  from sklearn import datasets
  from sklearn.base import BaseEstimator, ClassifierMixin, clone
  from sklearn.datasets import make_multilabel_classification
  from sklearn.dummy import DummyRegressor
  from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor, VotingClassifier, VotingRegressor
  from sklearn.exceptions import NotFittedError
  from sklearn.linear_model import LinearRegression, LogisticRegression
  from sklearn.model_selection import GridSearchCV, cross_val_score, train_test_split
  from sklearn.multiclass import OneVsRestClassifier
  from sklearn.naive_bayes import GaussianNB
  from sklearn.neighbors import KNeighborsClassifier
  from sklearn.preprocessing import StandardScaler
  from sklearn.svm import SVC
  from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
  from sklearn.utils._testing import assert_almost_equal, assert_array_almost_equal, assert_array_equal
label_desc: Use image node_id 10 for calling a global function with example usage: test_multilabel() without return types