code: def test_multiclass_multioutput_estimator():
      # test to check meta of meta estimators
      svc = LinearSVC(dual="auto", random_state=0)
      multi_class_svc = OneVsRestClassifier(svc)
      multi_target_svc = MultiOutputClassifier(multi_class_svc)
  
      multi_target_svc.fit(X, y)
  
      predictions = multi_target_svc.predict(X)
      assert (n_samples, n_outputs) == predictions.shape
  
      # train the forest with each column and assert that predictions are equal
      for i in range(3):
          multi_class_svc_ = clone(multi_class_svc)  # create a clone
          multi_class_svc_.fit(X, y[:, i])
          assert list(multi_class_svc_.predict(X)) == list(
              predictions[:, i]
          )
  
imports: import re
  import numpy
  import pytest
  from joblib import cpu_count
  from sklearn import datasets
  from sklearn.base import ClassifierMixin, clone
  from sklearn.datasets import load_linnerud, make_classification, make_multilabel_classification, make_regression
  from sklearn.dummy import DummyClassifier, DummyRegressor
  from sklearn.ensemble import GradientBoostingRegressor, RandomForestClassifier, StackingRegressor
  from sklearn.exceptions import NotFittedError
  from sklearn.impute import SimpleImputer
  from sklearn.linear_model import Lasso, LinearRegression, LogisticRegression, OrthogonalMatchingPursuit, PassiveAggressiveClassifier, Ridge, SGDClassifier, SGDRegressor
  from sklearn.metrics import jaccard_score, mean_squared_error
  from sklearn.model_selection import GridSearchCV, train_test_split
  from sklearn.multiclass import OneVsRestClassifier
  from sklearn.multioutput import ClassifierChain, MultiOutputClassifier, MultiOutputRegressor, RegressorChain
  from sklearn.pipeline import make_pipeline
  from sklearn.svm import LinearSVC
  from sklearn.tree import DecisionTreeClassifier
  from sklearn.utils import shuffle
  from sklearn.utils._testing import assert_almost_equal, assert_array_almost_equal, assert_array_equal
  from sklearn.utils.fixes import BSR_CONTAINERS, COO_CONTAINERS, CSC_CONTAINERS, CSR_CONTAINERS, DOK_CONTAINERS, LIL_CONTAINERS
label_desc: Use image node_id 14 for calling a global function with example usage: test_multiclass_multioutput_estimator() without return types