code: def test_classifier(iris_train):
      X, y, feature_names, target_names = iris_train
      clf = LogisticRegression().fit(X, y)
      assert is_classifier(clf)
      perm = PermutationImportance(clf, random_state=42).fit(X, y)
      assert is_classifier(perm)
      assert (perm.classes_ == [0, 1, 2]).all()
      assert np.allclose(clf.predict(X), perm.predict(X))
      assert np.allclose(clf.predict_proba(X), perm.predict_proba(X))
      assert np.allclose(
          clf.predict_log_proba(X), perm.predict_log_proba(X)
      )
      assert np.allclose(
          clf.decision_function(X), perm.decision_function(X)
      )
  
imports: import pytest
  import numpy
  from sklearn.base import is_classifier, is_regressor
  from sklearn.svm import SVR, SVC
  from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier
  from sklearn.model_selection import train_test_split, cross_val_score
  from sklearn.pipeline import make_pipeline
  from sklearn.feature_selection import SelectFromModel
  from sklearn.linear_model import LogisticRegression
  import eli5
  from eli5.sklearn import PermutationImportance
  from .utils import format_as_all
label_desc: Use image node_id 8 for calling a global function with example usage: test_classifier(iris_train) without return types