code: def test_ts_parallel():
      exp = pt.TSForecastingExperiment()
  
      exp.setup(
          data_func=lambda: get_data("airline", verbose=False),
          fh=12,
          fold=3,
          fig_kwargs={"renderer": "notebook"},
          session_id=42,
      )
  
      test_models = exp.models().index.tolist()[:2]
  
      exp.compare_models(include=test_models, n_select=2)
      exp.compare_models(
          include=test_models, n_select=2, parallel=FugueBackend("dask")
      )
  
      fconf = {
          "fugue.rpc.server": "fugue.rpc.flask.FlaskRPCServer",  # keep this value
          "fugue.rpc.flask_server.host": "localhost",  # the driver ip address workers can access
          "fugue.rpc.flask_server.port": "3333",  # the open port on the dirver
          "fugue.rpc.flask_server.timeout": "2 sec",  # the timeout for worker to talk to driver
      }
  
      be = FugueBackend(
          "dask",
          fconf,
          display_remote=True,
          batch_size=1,
          top_only=False,
      )
      exp.compare_models(include=test_models, n_select=2, parallel=be)
  
      exp.pull()
  
imports: import pycaret.time_series
  from pycaret.datasets import get_data
  from pycaret.parallel import FugueBackend
label_desc: Use image node_id 1 for calling a global function with example usage: test_ts_parallel() without return types