code: def test_check_estimator_from_feature_engine(estimator):
      if estimator.__class__.__name__ == "ArbitraryDiscretiser":
          estimator.set_params(
              binning_dict={"var_1": [-np.Inf, 0, np.Inf]}
          )
      return check_feature_engine_estimator(estimator)
  
imports: import numpy
  import pytest
  from sklearn.utils.estimator_checks import check_estimator
  from feature_engine.discretisation import ArbitraryDiscretiser, DecisionTreeDiscretiser, EqualFrequencyDiscretiser, EqualWidthDiscretiser
  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