docstr: trend deltas for regularization.
  
  update if trend is modelled differently
docstr_tok: ["trend","deltas","for","regularization",".","update","if","trend","is","modelled","differently"]
code: def get_trend_deltas(self):
      """trend deltas for regularization.
  
      update if trend is modelled differently"""
      if (
          self.config_trend is None
          or self.config_trend.n_changepoints < 1
      ):
          trend_delta = None
      elif self.segmentwise_trend:
          trend_delta = self.trend_deltas[:, :, :] - torch.cat(
              (self.trend_k0, self.trend_deltas[:, :, 0:-1]), dim=2
          )
      else:
          trend_delta = self.trend_deltas
  
      return trend_delta
  
imports: import numpy
  import torch
  import torch.nn
  from neuralprophet.components.trend import Trend
  from neuralprophet.utils_torch import init_parameter
label_desc: Use image node_id 3 for calling the PiecewiseLinearTrend obj's underlying member method code with example usage: obj.get_trend_deltas() and returns: trend_delta