code: def test_ensemble_heterogeneous_estimators_all_dropped(
      X, y, estimator
  ):
      # check that we raise a consistent error when all estimators are
      # dropped
      estimator.set_params(lr="drop")
      with pytest.raises(
          ValueError, match="All estimators are dropped."
      ):
          estimator.fit(X, y)
  
file_path: scikit-learn/sklearn/ensemble/tests/test_common.py
imports: import numpy
  import pytest
  from sklearn.base import ClassifierMixin, clone, is_classifier
  from sklearn.datasets import load_diabetes, load_iris, make_classification, make_regression
  from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor, StackingClassifier, StackingRegressor, VotingClassifier, VotingRegressor
  from sklearn.impute import SimpleImputer
  from sklearn.linear_model import LinearRegression, LogisticRegression
  from sklearn.pipeline import make_pipeline
  from sklearn.svm import SVC, SVR, LinearSVC, LinearSVR
label_desc: Use image node_id 4 for calling a global function with example usage: test_ensemble_heterogeneous_estimators_all_dropped(X, y, estimator) without return types