docstr: If lags were specified in a component-wise manner, they are contained in self.component_lags and
  the values in self.lags should be ignored as they correspond just the extreme values.
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code: def _get_lags(self, lags_type: str):
      """
      If lags were specified in a component-wise manner, they are contained in self.component_lags and
      the values in self.lags should be ignored as they correspond just the extreme values.
      """
      if lags_type in self.component_lags:
          return self.component_lags[lags_type]
      else:
          return self.lags.get(lags_type, None)
  
imports: from collections import OrderedDict
  from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple, Union
  import numpy
  import pandas
  from sklearn.linear_model import LinearRegression
  from darts.logging import get_logger, raise_if, raise_if_not, raise_log
  from darts.models.forecasting.forecasting_model import GlobalForecastingModel
  from darts.timeseries import TimeSeries
  from darts.utils.data.tabularization import add_static_covariates_to_lagged_data, create_lagged_component_names, create_lagged_training_data
  from darts.utils.historical_forecasts import _check_optimizable_historical_forecasts_global_models, _optimized_historical_forecasts_all_points, _optimized_historical_forecasts_last_points_only, _process_historical_forecast_input
  from darts.utils.multioutput import MultiOutputRegressor
  from darts.utils.utils import _check_quantiles, get_single_series, seq2series, series2seq
label_desc: Use image node_id 3 for calling the RegressionModel obj's underlying member method code with example usage: obj._get_lags(lags_type) and returns: self, self