code: def test_regression_auto_start_multiple_no_cov(self, config):
      train_length = 15
      forecast_horizon = 10
      model_cls, kwargs, model_kwargs, bounds = config
      model = model_cls(
          **kwargs,
          **model_kwargs,
      )
      model.fit(self.ts_pass_train)
  
      forecasts = model.historical_forecasts(
          series=[self.ts_pass_val, self.ts_pass_val],
          forecast_horizon=forecast_horizon,
          train_length=train_length,
          stride=1,
          retrain=True,
          overlap_end=False,
      )
  
      assert (
          len(forecasts) == 2
      ), f"Model {model_cls} did not return a list of historical forecasts"
  
      theorical_forecast_length = (
          self.ts_val_length
          - max(
              [
                  (
                      bounds[0] + bounds[1] + 1
                  ),  # +1 as sklearn models require min 2 train samples
                  train_length,
              ]
          )  # because we train
          - forecast_horizon  # because we have overlap_end = False
          + 1  # because we include the first element
      )
  
      assert (
          len(forecasts[0])
          == len(forecasts[1])
          == theorical_forecast_length
      ), (
          f"Model {model_cls.__name__} does not return the right number of historical forecasts in the case "
          f"of retrain=True and overlap_end=False, and a time index of type DateTimeIndex. "
          f"Expected {theorical_forecast_length}, got {len(forecasts[0])} and {len(forecasts[1])}"
      )
  
imports: import itertools
  from itertools import product
  import numpy
  import pandas
  import pytest
  import darts
  from darts import TimeSeries, concatenate
  from darts.dataprocessing.transformers import Scaler
  from darts.datasets import AirPassengersDataset
  from darts.logging import get_logger
  from darts.models import ARIMA, AutoARIMA, CatBoostModel, LightGBMModel, LinearRegressionModel, NaiveSeasonal, NotImportedModule
  from darts.tests.conftest import tfm_kwargs
  from darts.utils import timeseries_generation
label_desc: Use image node_id 9 for calling the TestHistoricalforecast obj's underlying member method code with example usage: obj.test_regression_auto_start_multiple_no_cov(config) without return types