code: def test_make_evaluation_predictions_zero(freq):
      prediction_length = 5
      ts_length = 50
  
      predictor = IdentityPredictor(
          prediction_length=prediction_length, num_samples=5
      )
      dataset = [
          dict(
              start=pd.Period("2010-01-01 00:00", freq=freq) + k,
              target=np.arange(start=k, stop=k + ts_length),
          )
          for k in range(10)
      ]
  
      forecasts, tss = make_evaluation_predictions(dataset, predictor)
  
      for k, (forecast, ts) in enumerate(zip(forecasts, tss)):
          assert np.allclose(
              forecast.median,
              np.arange(
                  start=ts_length - 2 * prediction_length + k,
                  stop=ts_length - prediction_length + k,
              ),
          )
          assert isinstance(ts, pd.DataFrame)
          assert isinstance(ts.index, pd.PeriodIndex)
          assert ts.index[0] == dataset[k]["start"]
          assert ts.shape[0] == len(dataset[k]["target"])
          assert np.allclose(
              ts.iloc[:, 0].values,
              np.arange(start=k, stop=k + ts_length),
          )
  
imports: import numpy
  import pandas
  import pytest
  from gluonts.evaluation.backtest import make_evaluation_predictions
  from gluonts.model.trivial.identity import IdentityPredictor
label_desc: Use image node_id 1 for calling a global function with example usage: test_make_evaluation_predictions_zero(freq) without return types