code: def fit(self, series: TimeSeries):
      super().fit(series)
      self._assert_univariate(series)
      series = self.training_series
      self.model.fit(
          series.values(copy=False).flatten(),
      )
      return self
  
file_path: darts/darts/models/forecasting/sf_auto_theta.py
imports: from statsforecast.models import AutoTheta
  from darts import TimeSeries
  from darts.models.components.statsforecast_utils import create_normal_samples, one_sigma_rule, unpack_sf_dict
  from darts.models.forecasting.forecasting_model import LocalForecastingModel
label_desc: Use image node_id 2 for calling the StatsForecastAutoTheta obj's underlying member method code with example usage: obj.fit(series) and returns: self