code: def test_layer_params_estimator():
      """[Module | LayerEnsemble] test set params on estimator"""
      est.fit(X, y)
  
      # Just a check that this works
      out = est.get_params()
      assert isinstance(out, dict)
  
      est.set_params(**{"offs-1__estimator__offset": 10})
      np.testing.assert_warns(ParameterChangeWarning, est.predict, X)
  
imports: import numpy
  from mlens.index import FullIndex, FoldIndex
  from mlens.testing import Data
  from mlens.testing.dummy import ESTIMATORS, PREPROCESSING
  from mlens.utils.dummy import OLS, Scale
  from mlens.utils.exceptions import NotFittedError, ParameterChangeWarning
  from mlens.parallel import make_group
  from mlens.estimators import LearnerEstimator, TransformerEstimator, LayerEnsemble
  from mlens.externals.sklearn.base import clone
label_desc: Use image node_id 5 for calling a global function with example usage: test_layer_params_estimator() without return types