code: def test_score_samples():
      X_train = [[1, 1], [1, 2], [2, 1]]
      clf1 = IsolationForest(contamination=0.1).fit(X_train)
      clf2 = IsolationForest().fit(X_train)
      assert_array_equal(
          clf1.score_samples([[2.0, 2.0]]),
          clf1.decision_function([[2.0, 2.0]]) + clf1.offset_,
      )
      assert_array_equal(
          clf2.score_samples([[2.0, 2.0]]),
          clf2.decision_function([[2.0, 2.0]]) + clf2.offset_,
      )
      assert_array_equal(
          clf1.score_samples([[2.0, 2.0]]),
          clf2.score_samples([[2.0, 2.0]]),
      )
  
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 12 for calling a global function with example usage: test_score_samples() without return types