code: def test_check_estimator_from_feature_engine(estimator):
      if estimator.__class__.__name__ == "CategoricalImputer":
          estimator.set_params(ignore_format=False)
      if estimator.__class__.__name__ in [
          "DropMissingData",
          "AddMissingIndicator",
      ]:
          estimator.set_params(missing_only=False)
      return check_feature_engine_estimator(estimator)
  
imports: import pytest
  from sklearn.utils.estimator_checks import check_estimator
  from feature_engine.imputation import AddMissingIndicator, ArbitraryNumberImputer, CategoricalImputer, DropMissingData, EndTailImputer, MeanMedianImputer, RandomSampleImputer
  from tests.estimator_checks.estimator_checks import check_feature_engine_estimator
label_desc: Use image node_id 2 for calling a global function with example usage: test_check_estimator_from_feature_engine(estimator) and returns: check_feature_engine_estimator