code: def test_call_backtest_regression_ensemble_local_models(self):
      regr_train_n = 10
      ensemble = RegressionEnsembleModel(
          [NaiveSeasonal(5), Theta(2, 5)],
          regression_train_n_points=regr_train_n,
      )
      ensemble.fit(self.sine_series)
      assert (
          max(
              m_.min_train_series_length
              for m_ in ensemble.forecasting_models
          )
          == 10
      )
      # -10 comes from the maximum minimum train series length of all models
      assert ensemble.extreme_lags == (
          -10 - regr_train_n,
          -1,
          None,
          None,
          None,
          None,
      )
      ensemble.backtest(self.sine_series)
  
imports: from typing import List, Union
  import numpy
  import pandas
  import pytest
  from sklearn.ensemble import RandomForestRegressor
  from sklearn.linear_model import LinearRegression
  from darts import TimeSeries
  from darts.logging import get_logger
  from darts.metrics import mape, rmse
  from darts.models import LinearRegressionModel, NaiveDrift, NaiveSeasonal, RandomForest, RegressionEnsembleModel, RegressionModel, Theta
  from darts.tests.conftest import tfm_kwargs
  from darts.tests.models.forecasting.test_ensemble_models import _make_ts
  from darts.tests.models.forecasting.test_regression_models import train_test_split
  from darts.utils import timeseries_generation
label_desc: Use image node_id 20 for calling the TestRegressionEnsembleModels obj's underlying member method code with example usage: obj.test_call_backtest_regression_ensemble_local_models() without return types