code: def __init__(
      self,
      config,
      id_list,
      quantiles,
      num_trends_modelled,
      n_forecasts,
      device,
  ):
      super().__init__(
          n_forecasts=n_forecasts,
          quantiles=quantiles,
          id_list=id_list,
          device=device,
      )
      self.config_trend = config
      self.num_trends_modelled = num_trends_modelled
  
      # if only 1 time series, global strategy
      if len(self.id_list) == 1:
          self.config_trend.trend_global_local = "global"
  
      # dimensions  - [no. of quantiles, 1 bias shape]
      self.bias = init_parameter(
          dims=[
              len(self.quantiles),
          ]
      )
  
file_path: neural_prophet/neuralprophet/components/trend/base.py
imports: from abc import abstractmethod
  from neuralprophet.components import BaseComponent
  from neuralprophet.utils_torch import init_parameter
label_desc: Use image node_id 1 to create a new Trend object from inherited base classes: BaseComponent with example: obj = Trend(config, id_list, quantiles, num_trends_modelled, n_forecasts, device)