code: def test_range_fh_in_predict():
      """Test using ``range`` in ``predict``."""
      test_dataset = _make_panel(n_instances=10, n_columns=5)
  
      var_model = VAR().fit(test_dataset)
  
      with pytest.raises(
          ValueError,
          match=(
              "The forecasting horizon `fh` must be passed either to `fit` or `predict`,"
              " but was found in neither."
          ),
      ):
          _ = var_model.predict()
  
      var_predictions = var_model.predict(fh=range(1, 2 + 1))
  
      assert isinstance(var_predictions, pd.DataFrame)
      assert var_predictions.shape == (10 * 2, 5)
  
imports: from functools import reduce
  from operator import mul
  import numpy
  import pandas
  import pytest
  from pandas.testing import assert_series_equal
  from sktime.datatypes import check_is_mtype, convert
  from sktime.datatypes._utilities import get_cutoff, get_window
  from sktime.forecasting.arima import ARIMA
  from sktime.forecasting.naive import NaiveForecaster
  from sktime.forecasting.theta import ThetaForecaster
  from sktime.forecasting.var import VAR
  from sktime.utils._testing.hierarchical import _make_hierarchical
  from sktime.utils._testing.panel import _make_panel
  from sktime.utils._testing.series import _make_series
  from sktime.utils.parallel import _get_parallel_test_fixtures
  from sktime.utils.validation._dependencies import _check_estimator_deps
label_desc: Use image node_id 13 for calling a global function with example usage: test_range_fh_in_predict() without return types