code: def test_sklearn_compatible_wrapper(estimator, check):
      check(estimator)
  
file_path: feature_engine/tests/check_estimators_with_parametrize_tests.py
imports: from sklearn.impute import SimpleImputer
  from sklearn.linear_model import LogisticRegression
  from sklearn.utils.estimator_checks import parametrize_with_checks
  from feature_engine.encoding import CountFrequencyEncoder, DecisionTreeEncoder, MeanEncoder, OneHotEncoder, OrdinalEncoder, PRatioEncoder, RareLabelEncoder, WoEEncoder
  from feature_engine.imputation import AddMissingIndicator, ArbitraryNumberImputer, CategoricalImputer, DropMissingData, EndTailImputer, MeanMedianImputer, RandomSampleImputer
  from feature_engine.outliers import ArbitraryOutlierCapper, OutlierTrimmer, Winsorizer
  from feature_engine.selection import DropConstantFeatures, DropCorrelatedFeatures, DropDuplicateFeatures, DropFeatures, DropHighPSIFeatures, RecursiveFeatureAddition, RecursiveFeatureElimination, SelectByShuffling, SelectBySingleFeaturePerformance, SelectByTargetMeanPerformance, SmartCorrelatedSelection
  from feature_engine.timeseries.forecasting import LagFeatures
  from feature_engine.transformation import BoxCoxTransformer, LogTransformer, PowerTransformer, ReciprocalTransformer, YeoJohnsonTransformer
  from feature_engine.wrappers import SklearnTransformerWrapper
label_desc: Use image node_id 6 for calling a global function with example usage: test_sklearn_compatible_wrapper(estimator, check) without return types