code: def _predict(
      self,
      n: int,
      future_covariates: Optional[TimeSeries] = None,
      num_samples: int = 1,
      verbose: bool = False,
  ):
      super()._predict(n, future_covariates, num_samples)
      forecast = self.model.predict(
          n_periods=n,
          X=future_covariates.values() if future_covariates else None,
      )
      return self._build_forecast_series(forecast)
  
file_path: darts/darts/models/forecasting/auto_arima.py
imports: from typing import Optional
  from pmdarima import AutoARIMA
  from darts.logging import get_logger, raise_if
  from darts.models.forecasting.forecasting_model import FutureCovariatesLocalForecastingModel
  from darts.timeseries import TimeSeries
label_desc: Use image node_id 4 for calling the AutoARIMA obj's underlying member method code with example usage: obj._predict(n, future_covariates, num_samples, verbose) and returns: self