docstr: Predict using the best model after HPO.
  
  :param horizon: the number of steps forward to predict
  :param freq: the freqency of the predicted dataframe, defaulted to day("D"),
         the frequency can be anything from the pandas list of frequency strings here:
         https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#timeseries-offset-aliases
  :param ds_data: a dataframe that has 1 column 'ds' indicating date.
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code: def predict(self, horizon=1, freq="D", ds_data=None):
      """
      Predict using the best model after HPO.
  
      :param horizon: the number of steps forward to predict
      :param freq: the freqency of the predicted dataframe, defaulted to day("D"),
             the frequency can be anything from the pandas list of frequency strings here:
             https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#timeseries-offset-aliases
      :param ds_data: a dataframe that has 1 column 'ds' indicating date.
      """
      from bigdl.nano.utils.common import invalidInputError
  
      if self.best_model.model is None:
          invalidInputError(
              False,
              "You must call fit or restore first before calling predict!",
          )
      return self.best_model.predict(
          horizon=horizon, freq=freq, ds_data=ds_data
      )
  
file_path: BigDL/python/chronos/src/bigdl/chronos/autots/model/auto_prophet.py
imports: import pandas
  import warnings
  from bigdl.chronos.model.prophet import ProphetBuilder, ProphetModel
  from bigdl.chronos.autots.utils import recalculate_n_sampling
label_desc: Use image node_id 3 for calling the AutoProphet obj's underlying member method code with example usage: obj.predict(horizon, freq, ds_data) and returns: self