code: def __init__(
      self,
      config,
      id_list,
      quantiles,
      n_forecasts,
      device,
      config_trend_none_bool,
  ):
      super().__init__(
          n_forecasts=n_forecasts,
          quantiles=quantiles,
          id_list=id_list,
          device=device,
      )
  
      self.config_regressors = config  # config_regressors
      self.regressors_dims = utils.config_regressors_to_model_dims(
          config
      )  # config_regressors
      if self.regressors_dims is not None:
          self.n_additive_regressor_params = 0
          self.n_multiplicative_regressor_params = 0
          for name, configs in self.regressors_dims.items():
              if configs["mode"] not in ["additive", "multiplicative"]:
                  log.error(
                      "Regressors mode {} not implemented. Defaulting to 'additive'.".format(
                          configs["mode"]
                      )
                  )
                  self.regressors_dims[name]["mode"] = "additive"
              if configs["mode"] == "additive":
                  self.n_additive_regressor_params += 1
              elif configs["mode"] == "multiplicative":
                  if config_trend_none_bool:
                      log.error(
                          "Multiplicative regressors require trend."
                      )
                      raise ValueError
                  self.n_multiplicative_regressor_params += 1
  
      else:
          self.config_regressors = None
  
imports: import logging
  from neuralprophet import utils
  from neuralprophet.components import BaseComponent
label_desc: Use image node_id 1 to create a new FutureRegressors object from inherited base classes: BaseComponent with example: obj = FutureRegressors(config, id_list, quantiles, n_forecasts, device, config_trend_none_bool)