code: def _eval_cross_validation(self, expected_horizon):
      df_cv = cross_validation(self.model, horizon=expected_horizon)
      df_p = performance_metrics(
          df_cv, metrics=[self.metric], rolling_window=1
      )
      return {self.metric: np.mean(df_p[self.metric].values)}
  
file_path: BigDL/python/chronos/src/bigdl/chronos/model/prophet.py
imports: import json
  import numpy
  from prophet import Prophet
  from prophet.serialize import model_to_json, model_from_json
  from prophet.diagnostics import performance_metrics
  from prophet.diagnostics import cross_validation
  from bigdl.chronos.metric.forecast_metrics import Evaluator
label_desc: Use image node_id 5 for calling the ProphetModel obj's underlying member method code with example usage: obj._eval_cross_validation(expected_horizon) and returns: dict