code: def test_nofreq_pass():
      """Test that recursive reducers return same results with / without freq given."""
      regressor = make_pipeline(
          LinearRegression(),
      )
  
      kwargs = {
          "lag_feature": {
              "lag": [1],
          }
      }
  
      forecaster_global = make_reduction(
          regressor,
          scitype="tabular-regressor",
          transformers=[
              WindowSummarizer(**kwargs, n_jobs=1, truncate="bfill")
          ],
          window_length=None,
          strategy="recursive",
          pooling="global",
      )
  
      forecaster_global_freq = make_reduction(
          regressor,
          scitype="tabular-regressor",
          transformers=[
              WindowSummarizer(**kwargs, n_jobs=1, truncate="bfill")
          ],
          window_length=None,
          strategy="recursive",
          pooling="global",
      )
  
      y = _make_hierarchical(
          hierarchy_levels=(100,),
          min_timepoints=1000,
          max_timepoints=1000,
      )
  
      y_no_freq = y.reset_index().set_index(["h0", "time"])
  
      forecaster_global.fit(y)
      forecaster_global_freq.fit(y_no_freq)
  
      y_pred_global = forecaster_global.predict(fh=[1, 2])
      y_pred_nofreq = forecaster_global_freq.predict(fh=[1, 2])
      np.testing.assert_almost_equal(
          y_pred_global["c0"].values, y_pred_nofreq["c0"].values
      )
  
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 7 for calling a global function with example usage: test_nofreq_pass() without return types