code: def _split_multi_ts_sequence(
      self, n: Union[int, List[int]], ts_sequence: Sequence[TimeSeries]
  ) -> Tuple[Sequence[TimeSeries], Sequence[TimeSeries]]:
      if isinstance(n, int):
          n = [n] * len(ts_sequence)
      left = [ts[:-n_] for ts, n_ in zip(ts_sequence, n)]
      right = [ts[-n_:] for ts, n_ in zip(ts_sequence, n)]
      return left, right
  
file_path: darts/darts/models/forecasting/regression_ensemble_model.py
imports: from typing import List, Optional, Sequence, Tuple, Union
  from darts.logging import get_logger, raise_if, raise_if_not
  from darts.models.forecasting.ensemble_model import EnsembleModel
  from darts.models.forecasting.forecasting_model import ForecastingModel
  from darts.models.forecasting.linear_regression_model import LinearRegressionModel
  from darts.models.forecasting.regression_model import RegressionModel
  from darts.timeseries import TimeSeries, concatenate
  from darts.utils.utils import seq2series, series2seq
label_desc: Use image node_id 2 for calling the RegressionEnsembleModel obj's underlying member method code with example usage: obj._split_multi_ts_sequence(n, ts_sequence) and returns: left,  right