code: def test_sklearn_composite_classifiers(
      data_args, composite_classifier
  ):
      """Test if sklearn composite classifiers can handle sktime data and classifiers."""
      fit_args = make_classification_problem(**data_args)
      composite_classifier.fit(*fit_args)
  
      X = _make_panel_X(**data_args)
      preds = composite_classifier.predict(X=X)
      assert isinstance(preds, np.ndarray)
  
file_path: sktime/sktime/classification/tests/test_sklearn_compatibility.py
imports: import numpy
  import pytest
  from sklearn.calibration import CalibratedClassifierCV
  from sklearn.ensemble import VotingClassifier
  from sklearn.experimental import enable_halving_search_cv
  from sklearn.model_selection import GridSearchCV, GroupKFold, GroupShuffleSplit, KFold, LeaveOneOut, LeavePGroupsOut, LeavePOut, RandomizedSearchCV, RepeatedKFold, ShuffleSplit, StratifiedKFold, StratifiedShuffleSplit, TimeSeriesSplit, cross_val_score
  from sklearn.pipeline import Pipeline
  from sktime.classification.interval_based import CanonicalIntervalForest
  from sktime.transformations.panel.pca import PCATransformer
  from sktime.utils._testing.panel import _make_panel_X, make_classification_problem
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 4 for calling a global function with example usage: test_sklearn_composite_classifiers(data_args, composite_classifier) without return types