code: def test_sparse():
      """[Parallel] Test sparse feature propagation."""
      out_1 = ens2.fit(X, y, return_preds=True)
      Z = csr_matrix(X)
      out_2 = ens3.fit(Z, y, return_preds=True)
      np.testing.assert_allclose(
          out_1, out_2.toarray().astype(dtype=np.float32)
      )
  
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 5 for calling a global function with example usage: test_sparse() without return types