docstr: Predict horizon time-points ahead the input x in fit_eval
  :param x: We don't support input x currently.
  :param horizon: horizon length to predict
  :param mc:
  :return:
docstr_tok: ["Predict","horizon","time-points","ahead","the","input","x","in","fit_eval",":","param","x",":","We","do","n't","support","input","x","currently",".",":","param","horizon",":","horizon","length","to","predict",":","param","mc",":",":","return",":"]
code: def predict(self, x):
      """
      Predict horizon time-points ahead the input x in fit_eval
      :param x: We don't support input x currently.
      :param horizon: horizon length to predict
      :param mc:
      :return:
      """
      if x is None:
          invalidInputError(False, "Input invalid x of None")
      if self.model is None:
          invalidInputError(
              False,
              "Needs to call fit_eval or restore first before calling predict",
          )
      self.model.n_jobs = self.n_jobs
      out = self.model.predict(x)
      return out
  
imports: from bigdl.orca.common import SafePickle
  import pandas
  from xgboost.sklearn import XGBRegressor
  from xgboost.sklearn import XGBClassifier
  from bigdl.orca.automl.metrics import Evaluator
  from bigdl.orca.automl.model.abstract import BaseModel, ModelBuilder
  from bigdl.dllib.utils.log4Error import invalidInputError
  import logging
label_desc: Use image node_id 6 for calling the XGBoost obj's underlying member method code with example usage: obj.predict(x) and returns: out