code: def fit(self, series: TimeSeries):
      super().fit(series)
  
      raise_if_not(
          len(series) >= self.K,
          f"The time series requires at least K={self.K} points",
          logger,
      )
      self.last_k_vals = series.values(copy=False)[-self.K :, :]
      return self
  
imports: from typing import List, Optional, Sequence, Union
  import numpy
  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, LocalForecastingModel
  from darts.timeseries import TimeSeries
label_desc: Use image node_id 4 for calling the NaiveSeasonal obj's underlying member method code with example usage: obj.fit(series) and returns: self