code: def test_output_backtesting_forecaster_multiseries_ForecasterAutoregMultiSeries_refit_with_mocked(
      forecaster, n_jobs
  ):
      """
      Test output of backtesting_forecaster_multiseries in ForecasterAutoregMultiSeries
      and ForecasterAutoregMultiSeriesCustom with refit with mocked
      (mocked done in Skforecast v0.5.0).
      """
  
      steps = 3
      n_validation = 12
  
      (
          metrics_levels,
          backtest_predictions,
      ) = backtesting_forecaster_multiseries(
          forecaster=forecaster,
          series=series,
          steps=steps,
          levels="l1",
          metric="mean_absolute_error",
          initial_train_size=len(series) - n_validation,
          refit=True,
          fixed_train_size=False,
          exog=None,
          interval=None,
          n_boot=500,
          random_state=123,
          in_sample_residuals=True,
          verbose=False,
          n_jobs=n_jobs,
      )
  
      expected_metric = pd.DataFrame(
          {
              "levels": ["l1"],
              "mean_absolute_error": [0.2124129141233719],
          }
      )
      expected_predictions = pd.DataFrame(
          {
              "l1": np.array(
                  [
                      0.4978838984103099,
                      0.46288426670127997,
                      0.48433446479429937,
                      0.510664891759972,
                      0.49734477162307983,
                      0.5009680695304023,
                      0.48647770856843825,
                      0.4884651517014008,
                      0.48643766346259326,
                      0.4973047492523979,
                      0.4899104838474172,
                      0.4891085370228432,
                  ]
              )
          },
          index=pd.RangeIndex(start=38, stop=50, step=1),
      )
  
      pd.testing.assert_frame_equal(expected_metric, metrics_levels)
      pd.testing.assert_frame_equal(
          expected_predictions, backtest_predictions
      )
  
imports: import re
  import pytest
  import numpy
  import pandas
  from sklearn.linear_model import Ridge
  from sklearn.metrics import mean_absolute_error
  from skforecast.exceptions import IgnoredArgumentWarning
  from skforecast.ForecasterAutoreg import ForecasterAutoreg
  from skforecast.ForecasterAutoregMultiSeries import ForecasterAutoregMultiSeries
  from skforecast.ForecasterAutoregMultiSeriesCustom import ForecasterAutoregMultiSeriesCustom
  from skforecast.ForecasterAutoregMultiVariate import ForecasterAutoregMultiVariate
  from skforecast.model_selection_multiseries import backtesting_forecaster_multiseries
  from skforecast.model_selection_multiseries import backtesting_forecaster_multivariate
  from .fixtures_model_selection_multiseries import series
label_desc: Use image node_id 6 for calling a global function with example usage: test_output_backtesting_forecaster_multiseries_ForecasterAutoregMultiSeries_refit_with_mocked(forecaster, n_jobs) without return types