code: def test_is_multitarget_regressor():
      X, y = make_regression(n_targets=1)
      clf = ElasticNet()
      clf.fit(X, y)
      assert not is_multitarget_regressor(clf)
  
      X, y = make_regression(n_targets=2)
      clf = ElasticNet()
      clf.fit(X, y)
      assert is_multitarget_regressor(clf)
  
imports: from __future__ import absolute_import
  import numpy
  import pytest
  from sklearn.datasets import make_classification, make_regression
  from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer
  from sklearn.linear_model import LogisticRegression, ElasticNet, SGDRegressor
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.linear_model import SGDClassifier
  from sklearn.naive_bayes import GaussianNB, BernoulliNB
  from sklearn.tree import DecisionTreeClassifier
  from sklearn.multiclass import OneVsRestClassifier
  from eli5._feature_names import FeatureNames
  from eli5.sklearn.utils import get_feature_names, get_default_target_names, has_intercept, is_multiclass_classifier, is_multitarget_regressor, get_num_features
  from .utils import SGD_KWARGS
label_desc: Use image node_id 3 for calling a global function with example usage: test_is_multitarget_regressor() without return types