code: def test_propagation_three():
      """[Parallel] Test feature propagation from first layer prediction to second layer"""
      out_1 = ens1.fit(X, y, return_preds=True)
      out_2 = ens2.fit(X, y, return_preds=True)
      np.testing.assert_array_equal(
          out_2[:, n_first_prop:n_second_prop], out_1[:, n_first_prop:]
      )
  
file_path: mlens/mlens/parallel/tests/test_c_multi_sparse_feature_prop.py
imports: import numpy
  from scipy.sparse import csr_matrix
  from mlens.index import FoldIndex
  from mlens.ensemble.base import BaseEnsemble
  from mlens.externals.sklearn.validation import check_random_state
  from mlens.utils.dummy import OLS
label_desc: Use image node_id 4 for calling a global function with example usage: test_propagation_three() without return types