code: def test_historical_forecast(self, mode):
      model = self.models[1](lags=5, multi_models=mode)
      result = model.historical_forecasts(
          series=self.sine_univariate1,
          future_covariates=None,
          start=0.8,
          forecast_horizon=1,
          stride=1,
          retrain=True,
          overlap_end=False,
          last_points_only=True,
          verbose=False,
      )
      assert len(result) == 21
  
      model = self.models[1](
          lags=5, lags_past_covariates=5, multi_models=mode
      )
      result = model.historical_forecasts(
          series=self.sine_univariate1,
          past_covariates=self.sine_multivariate1,
          start=0.8,
          forecast_horizon=1,
          stride=1,
          retrain=True,
          overlap_end=False,
          last_points_only=True,
          verbose=False,
      )
      assert len(result) == 21
  
      model = self.models[1](
          lags=5,
          lags_past_covariates=5,
          output_chunk_length=5,
          multi_models=mode,
      )
      result = model.historical_forecasts(
          series=self.sine_univariate1,
          past_covariates=self.sine_multivariate1,
          start=0.8,
          forecast_horizon=1,
          stride=1,
          retrain=True,
          overlap_end=False,
          last_points_only=True,
          verbose=False,
      )
      assert len(result) == 21
  
imports: import copy
  import functools
  import itertools
  import math
  from unittest.mock import patch
  import numpy
  import pandas
  import pytest
  from sklearn.ensemble import HistGradientBoostingRegressor, RandomForestRegressor
  from sklearn.linear_model import LinearRegression
  import darts
  from darts import TimeSeries
  from darts.dataprocessing.encoders import FutureCyclicEncoder, PastDatetimeAttributeEncoder
  from darts.logging import get_logger
  from darts.metrics import mae, rmse
  from darts.models import CatBoostModel, LightGBMModel, LinearRegressionModel, NotImportedModule, RandomForest, RegressionModel, XGBModel
  from darts.utils import timeseries_generation
  from darts.utils.multioutput import MultiOutputRegressor
label_desc: Use image node_id 14 for calling the TestRegressionModels obj's underlying member method code with example usage: obj.test_historical_forecast(mode) without return types