code: def test_equality_transfo_nontranso(regressor):
      """Test that recursive reducers return same results for global / local forecasts."""
      y = load_airline()[:36]
      y_train, y_test = temporal_train_test_split(y, test_size=12)
      fh = ForecastingHorizon(y_test.index, is_relative=False)
  
      lag_vec = [i for i in range(6, 0, -1)]
      kwargs = {
          "lag_feature": {
              "lag": lag_vec,
          }
      }
  
      random_int = random.randint(1, 1000)
      regressor.random_state = random_int
      forecaster = make_reduction(
          regressor, window_length=int(6), strategy="recursive"
      )
      forecaster.fit(y_train)
      y_pred = forecaster.predict(fh)
      recursive_without = mean_absolute_percentage_error(
          y_test, y_pred, symmetric=False
      )
      forecaster = make_reduction(
          regressor,
          window_length=None,
          strategy="recursive",
          transformers=[WindowSummarizer(**kwargs, n_jobs=1)],
          pooling="global",
      )
  
      forecaster.fit(y_train)
      y_pred = forecaster.predict(fh)
      recursive_global = mean_absolute_percentage_error(
          y_test, y_pred, symmetric=False
      )
      np.testing.assert_almost_equal(
          recursive_without, recursive_global
      )
  
imports: from sktime.tests.test_switch import run_test_for_class
  from sktime.utils.validation._dependencies import _check_soft_dependencies
  import random
  import numpy
  import pandas
  import pytest
  from sklearn.ensemble import GradientBoostingRegressor, HistGradientBoostingRegressor, RandomForestRegressor
  from sklearn.linear_model import LinearRegression
  from sklearn.pipeline import make_pipeline
  from sktime.datasets import load_airline, load_solar
  from sktime.datatypes import get_examples
  from sktime.forecasting.base import ForecastingHorizon
  from sktime.forecasting.compose import make_reduction
  from sktime.forecasting.compose._reduce import _DirectReducer, _RecursiveReducer
  from sktime.performance_metrics.forecasting import mean_absolute_percentage_error
  from sktime.split import temporal_train_test_split
  from sktime.transformations.series.summarize import WindowSummarizer
  from sktime.utils._testing.hierarchical import _make_hierarchical
label_desc: Use image node_id 6 for calling a global function with example usage: test_equality_transfo_nontranso(regressor) without return types