code: def test_oneclass_adaboost_proba():
      # Test predict_proba robustness for one class label input.
      # In response to issue #7501
      # https://github.com/scikit-learn/scikit-learn/issues/7501
      y_t = np.ones(len(X))
      clf = AdaBoostClassifier(algorithm="SAMME").fit(X, y_t)
      assert_array_almost_equal(
          clf.predict_proba(X), np.ones((len(X), 1))
      )
  
imports: import re
  import numpy
  import pytest
  from sklearn import datasets
  from sklearn.base import BaseEstimator, clone
  from sklearn.dummy import DummyClassifier, DummyRegressor
  from sklearn.ensemble import AdaBoostClassifier, AdaBoostRegressor
  from sklearn.ensemble._weight_boosting import _samme_proba
  from sklearn.linear_model import LinearRegression
  from sklearn.model_selection import GridSearchCV, train_test_split
  from sklearn.svm import SVC, SVR
  from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
  from sklearn.utils import shuffle
  from sklearn.utils._mocking import NoSampleWeightWrapper
  from sklearn.utils._testing import assert_allclose, assert_array_almost_equal, assert_array_equal, assert_array_less
  from sklearn.utils.fixes import COO_CONTAINERS, CSC_CONTAINERS, CSR_CONTAINERS, DOK_CONTAINERS, LIL_CONTAINERS
label_desc: Use image node_id 2 for calling a global function with example usage: test_oneclass_adaboost_proba() without return types