code: def test_check_error_if_y_not_passed(estimator):
      return check_error_if_y_not_passed(estimator)
  
imports: import numpy
  import pandas
  import pytest
  from sklearn.base import clone
  from sklearn.exceptions import NotFittedError
  from sklearn.utils.estimator_checks import check_estimator
  from feature_engine._prediction.base_predictor import BaseTargetMeanEstimator
  from feature_engine._prediction.target_mean_classifier import TargetMeanClassifier
  from feature_engine._prediction.target_mean_regressor import TargetMeanRegressor
  from feature_engine.discretisation import EqualFrequencyDiscretiser, EqualWidthDiscretiser
  from feature_engine.encoding import MeanEncoder
  from tests.estimator_checks.dataframe_for_checks import test_df
  from tests.estimator_checks.fit_functionality_checks import check_error_if_y_not_passed
label_desc: Use image node_id 2 for calling a global function with example usage: test_check_error_if_y_not_passed(estimator) and returns: check_error_if_y_not_passed