code: def test_blend_with_larger_predict_fh():
      """Test to make sure that blending predictions work when the forecast horizon
      used in predictions is larger than the one used for training
      Ref: https://github.com/pycaret/pycaret/issues/2329
      """
      data = get_data("airline", verbose=False)
  
      exp = TSForecastingExperiment()
      exp.setup(data=data, fh=12, fold=2, session_id=42)
      model1 = exp.create_model("naive")
      model2 = exp.create_model("ets")
      model3 = exp.create_model("lr_cds_dt")
      blender = exp.blend_models([model1, model2, model3])
  
      # Check that forecasts can be created for FH greater than the one used for training
      FHs = [12, 24]
      for fh in FHs:
          preds = exp.predict_model(blender, fh=fh)
          assert len(preds) == fh
  
file_path: pycaret/tests/test_time_series_blending.py
imports: import random
  import numpy
  import pandas
  import pytest
  from pycaret.datasets import get_data
  from pycaret.time_series import TSForecastingExperiment
label_desc: Use image node_id 5 for calling a global function with example usage: test_blend_with_larger_predict_fh() without return types