code: def test_rfe_importance_getter_validation(
      importance_getter, err_type, Selector
  ):
      X, y = make_friedman1(
          n_samples=50, n_features=10, random_state=42
      )
      estimator = LinearSVR(dual="auto")
      log_estimator = TransformedTargetRegressor(
          regressor=estimator, func=np.log, inverse_func=np.exp
      )
  
      with pytest.raises(err_type):
          model = Selector(
              log_estimator, importance_getter=importance_getter
          )
          model.fit(X, y)
  
imports: from operator import attrgetter
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_array_equal
  from sklearn.base import BaseEstimator, ClassifierMixin
  from sklearn.compose import TransformedTargetRegressor
  from sklearn.cross_decomposition import CCA, PLSCanonical, PLSRegression
  from sklearn.datasets import load_iris, make_friedman1
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.feature_selection import RFE, RFECV
  from sklearn.impute import SimpleImputer
  from sklearn.linear_model import LogisticRegression
  from sklearn.metrics import get_scorer, make_scorer, zero_one_loss
  from sklearn.model_selection import GroupKFold, cross_val_score
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import StandardScaler
  from sklearn.svm import SVC, SVR, LinearSVR
  from sklearn.utils import check_random_state
  from sklearn.utils._testing import ignore_warnings
  from sklearn.utils.fixes import CSR_CONTAINERS
label_desc: Use image node_id 16 for calling a global function with example usage: test_rfe_importance_getter_validation(importance_getter, err_type, Selector) without return types