code: def test_paramplugin_dict():
      """Test PluginParamsForecaster with param: dict.
  
      Failure case from bug report #4921.
      """
      from sklearn.ensemble import RandomForestRegressor
  
      from sktime.forecasting.base import ForecastingHorizon
      from sktime.forecasting.compose import (
          EnsembleForecaster,
          make_reduction,
      )
      from sktime.forecasting.model_selection import (
          ForecastingGridSearchCV,
      )
      from sktime.split import ExpandingWindowSplitter
  
      y, X = load_longley()
      horizon = ForecastingHorizon(np.arange(1, 4), is_relative=True)
  
      random_forest = make_reduction(
          RandomForestRegressor(),
          window_length=2,
          strategy="direct",
          windows_identical=False,
      )
      expanding_window_cv = ExpandingWindowSplitter(
          fh=horizon, step_length=1
      )
      cv_random_forest = ForecastingGridSearchCV(
          forecaster=random_forest,
          cv=expanding_window_cv,
          param_grid={
              "estimator__max_features": np.linspace(0.1, 0.9, num=5)
          },
          return_n_best_forecasters=3,
      )
  
      ensembler = EnsembleForecaster(forecasters=[], aggfunc="median")
      plugin_fcst = PluginParamsForecaster(
          param_est=cv_random_forest,
          forecaster=ensembler,
          params={"forecasters": "n_best_forecasters"},
      )
  
      plugin_fcst.fit(y, X, fh=horizon)
      plugin_fcst.predict(fh=horizon, X=X)
  
file_path: sktime/sktime/param_est/tests/test_plugin.py
imports: import numpy
  import pytest
  from sktime.datasets import load_airline, load_longley
  from sktime.forecasting.naive import NaiveForecaster
  from sktime.param_est.fixed import FixedParams
  from sktime.param_est.plugin import PluginParamsForecaster
  from sktime.param_est.seasonality import SeasonalityACF
  from sktime.tests.test_switch import run_test_for_class
  from sktime.transformations.series.difference import Differencer
  from sktime.utils.validation._dependencies import _check_estimator_deps
label_desc: Use image node_id 2 for calling a global function with example usage: test_paramplugin_dict() without return types