code: def test_run():
      """[Blend] 'fit' and 'predict' runs correctly."""
      meta = OLS()
      meta.fit(F, y[5:])
      g = meta.predict(P)
  
      ens = TemporalEnsemble(step_size=5, window=10, lag=2)
      ens.add(ESTIMATORS, PREPROCESSING, dtype=np.float64)
      ens.add(OLS(), meta=True, dtype=np.float64)
  
      ens.fit(X, y)
  
      pred = ens.predict(X)
      np.testing.assert_array_equal(pred, g)
  
imports: import numpy
  from mlens.metrics import rmse
  from mlens.testing.dummy import Data, ESTIMATORS, PREPROCESSING, OLS
  from mlens.ensemble import TemporalEnsemble
label_desc: Use image node_id 1 for calling a global function with example usage: test_run() without return types