code: def test_names_not_unique(dummy_data):
      est = Stacking(
          _NoPredictDummy(),
          [
              ("m1", _PredictDummy()),
              ("m2", _PredictDummy()),
              ("m1", _PredictDummy()),
          ],
      )
      X, y = dummy_data
      with pytest.raises(
          ValueError,
          match=r"Names provided are not unique: \('m1', 'm2', 'm1'\)",
      ):
          est.fit(X, y)
  
imports: import numpy
  from numpy.testing import assert_array_almost_equal, assert_array_equal
  import pandas
  import pytest
  from sklearn.base import BaseEstimator
  from sklearn.datasets import load_iris
  from sklearn.linear_model import LogisticRegression
  from sklearn.metrics import accuracy_score, roc_auc_score
  from sklearn.svm import SVC
  from sklearn.tree import DecisionTreeClassifier
  from sksurv.ensemble import RandomSurvivalForest
  from sksurv.linear_model import CoxPHSurvivalAnalysis
  from sksurv.meta import MeanEstimator, Stacking
  from sksurv.svm import FastSurvivalSVM
  from sksurv.testing import assert_chf_properties, assert_cindex_almost_equal, assert_survival_function_properties
label_desc: Use image node_id 3 for calling the TestStackingClassifier obj's underlying member method code with example usage: obj.test_names_not_unique(dummy_data) without return types