code: def test_max_samples_consistency():
      # Make sure validated max_samples in iforest and BaseBagging are identical
      X = iris.data
      clf = IsolationForest().fit(X)
      assert clf.max_samples_ == clf._max_samples
  
imports: import warnings
  from unittest.mock import Mock, patch
  import numpy
  import pytest
  from sklearn.datasets import load_diabetes, load_iris, make_classification
  from sklearn.ensemble import IsolationForest
  from sklearn.ensemble._iforest import _average_path_length
  from sklearn.metrics import roc_auc_score
  from sklearn.model_selection import ParameterGrid, train_test_split
  from sklearn.utils import check_random_state
  from sklearn.utils._testing import assert_allclose, assert_array_almost_equal, assert_array_equal, ignore_warnings
  from sklearn.utils.fixes import CSC_CONTAINERS, CSR_CONTAINERS
label_desc: Use image node_id 9 for calling a global function with example usage: test_max_samples_consistency() without return types