docstr: Prediction.
  :param horizon
  :param future_covariates: covariates corresponding to future horizon steps data to predict.
  :param future_dti: dti corresponding to future horizon steps data to predict.
  :param num_workers
  :return: result
docstr_tok: ["Prediction",".",":","param","horizon",":","param","future_covariates",":","covariates","corresponding","to","future","horizon","steps","data","to","predict",".",":","param","future_dti",":","dti","corresponding","to","future","horizon","steps","data","to","predict",".",":","param","num_workers",":","return",":","result"]
code: def predict(
      self,
      horizon=24,
      future_covariates=None,
      future_dti=None,
      num_workers=None,
  ):
      """
      Prediction.
      :param horizon
      :param future_covariates: covariates corresponding to future horizon steps data to predict.
      :param future_dti: dti corresponding to future horizon steps data to predict.
      :param num_workers
      :return: result
      """
      pred = self.internal.predict(
          horizon=horizon,
          num_workers=num_workers,
          future_covariates=future_covariates,
          future_dti=future_dti,
      )
      result = dict()
      if self.id_arr is not None:
          result["id"] = self.id_arr
      result["prediction"] = pred
      return result
  
imports: from abc import ABCMeta, abstractmethod
  from zoo.chronos.model.tcmf import DeepGLO
  from zoo.orca.automl.metrics import Evaluator
  from zoo.orca.automl.model.abstract import BaseModel
  from zoo.orca.data import SparkXShards, XShards
  import pickle
  import numpy
  import pandas
label_desc: Use image node_id 6 for calling the TCMFNdarrayModelWrapper obj's underlying member method code with example usage: obj.predict(horizon, future_covariates, future_dti, num_workers) and returns: result