code: def test_internals():
      lr = LinearRegression()
      regressors = [lr, lr, lr, lr, lr]
      cv = 10
      stack = StackingCVRegressor(
          regressors=[lr, lr, lr, lr, lr],
          meta_regressor=lr,
          cv=cv,
          random_state=0,
      )
      stack.fit(X3, y3)
      assert stack.predict(X3).mean() == y3.mean()
      assert stack.meta_regr_.intercept_ == 0.0
      assert stack.meta_regr_.coef_[0] == 0.0
      assert stack.meta_regr_.coef_[1] == 0.0
      assert stack.meta_regr_.coef_[2] == 0.0
      assert len(stack.regr_) == len(regressors)
  
imports: import random
  import numpy
  import pytest
  from packaging.version import Version
  from scipy import sparse
  from sklearn import __version__
  from sklearn.base import clone
  from sklearn.linear_model import Lasso, LinearRegression, Ridge
  from sklearn.model_selection import GridSearchCV, KFold, train_test_split
  from sklearn.neighbors import KNeighborsRegressor
  from sklearn.svm import SVR
  from mlxtend.externals.estimator_checks import NotFittedError
  from mlxtend.regressor import StackingCVRegressor
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 5 for calling a global function with example usage: test_internals() without return types