code: def test_wrong_estimators_exceptions():
      X = np.array([[0.0]])
      y = np.array([0.0])
  
      with pytest.raises(
          ValueError, match="`classifier` has to be a classifier."
      ):
          zir = ZeroInflatedRegressor(
              ExtraTreesRegressor(), ExtraTreesRegressor()
          )
          zir.fit(X, y)
  
      with pytest.raises(
          ValueError, match="`regressor` has to be a regressor."
      ):
          zir = ZeroInflatedRegressor(
              ExtraTreesClassifier(), ExtraTreesClassifier()
          )
          zir.fit(X, y)
  
file_path: scikit-lego/tests/test_meta/test_zero_inflated_regressor.py
imports: import numpy
  import pytest
  from sklearn.ensemble import ExtraTreesClassifier, ExtraTreesRegressor
  from sklearn.neighbors import KNeighborsClassifier, KNeighborsRegressor
  from sklego.common import flatten
  from sklego.meta import ZeroInflatedRegressor
  from sklego.testing import check_shape_remains_same_regressor
  from tests.conftest import general_checks, regressor_checks, select_tests
label_desc: Use image node_id 5 for calling a global function with example usage: test_wrong_estimators_exceptions() without return types