code: def test_train_predict_global_models_multivar_with_covariates(self):
      ensemble_models = self.get_global_models(output_chunk_length=10)
      ensemble_models.append(
          RegressionModel(lags=1, lags_past_covariates=[-1])
      )
      ensemble = RegressionEnsembleModel(ensemble_models, 10)
      ensemble.fit(self.seq1, self.cov1)
      ensemble.predict(10, self.seq2, self.cov2)
  
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 13 for calling the TestRegressionEnsembleModels obj's underlying member method code with example usage: obj.test_train_predict_global_models_multivar_with_covariates() without return types