code: def test_calibration_without_sample_weight_estimator(data):
      """Check that even if the estimator doesn't support
      sample_weight, fitting with sample_weight still works.
  
      There should be a warning, since the sample_weight is not passed
      on to the estimator.
      """
      X, y = data
      sample_weight = np.ones_like(y)
  
      class ClfWithoutSampleWeight(CheckingClassifier):
          def fit(self, X, y, **fit_params):
              assert "sample_weight" not in fit_params
              return super().fit(X, y, **fit_params)
  
      clf = ClfWithoutSampleWeight()
      pc_clf = CalibratedClassifierCV(clf)
  
      with pytest.warns(UserWarning):
          pc_clf.fit(X, y, sample_weight=sample_weight)
  
imports: import numpy
  import pytest
  from numpy.testing import assert_allclose
  from sklearn.base import BaseEstimator, clone
  from sklearn.calibration import CalibratedClassifierCV, CalibrationDisplay, _CalibratedClassifier, _sigmoid_calibration, _SigmoidCalibration, calibration_curve
  from sklearn.datasets import load_iris, make_blobs, make_classification
  from sklearn.dummy import DummyClassifier
  from sklearn.ensemble import RandomForestClassifier, VotingClassifier
  from sklearn.exceptions import NotFittedError
  from sklearn.feature_extraction import DictVectorizer
  from sklearn.impute import SimpleImputer
  from sklearn.isotonic import IsotonicRegression
  from sklearn.linear_model import LogisticRegression, SGDClassifier
  from sklearn.metrics import brier_score_loss
  from sklearn.model_selection import KFold, LeaveOneOut, check_cv, cross_val_predict, cross_val_score, train_test_split
  from sklearn.naive_bayes import MultinomialNB
  from sklearn.pipeline import Pipeline, make_pipeline
  from sklearn.preprocessing import LabelEncoder, StandardScaler
  from sklearn.svm import LinearSVC
  from sklearn.tree import DecisionTreeClassifier
  from sklearn.utils._mocking import CheckingClassifier
  from sklearn.utils._testing import _convert_container, assert_almost_equal, assert_array_almost_equal, assert_array_equal
  from sklearn.utils.extmath import softmax
  from sklearn.utils.fixes import CSR_CONTAINERS
label_desc: Use image node_id 37 for calling a global function with example usage: test_calibration_without_sample_weight_estimator(data) and returns: super