docstr: w = self.w.tolist()
  intercept = None
  if self.init_param.get("fit_intercept"):
      w = w[:-1]
      intercept = w[-1]
docstr_tok: ["w","=","self.w.tolist","(",")","intercept","=","None","if","self.init_param.get","(","``","fit_intercept","''",")",":","w","=","w","[",":","-1","]","intercept","=","w","[","-1","]"]
code: def get_model(self):
      """w = self.w.tolist()
      intercept = None
      if self.init_param.get("fit_intercept"):
          w = w[:-1]
          intercept = w[-1]"""
      param = serialize_param(
          self.w, self.init_param.get("fit_intercept")
      )
      return {
          "param": param,
          # "intercept": intercept,
          "optimizer": self.optimizer.state_dict(),
          "lr_scheduler": self.lr_scheduler.state_dict(),
          "end_epoch": self.end_epoch,
          "is_converged": self.is_converged,
          "fit_intercept": self.init_param.get("fit_intercept"),
          "header": self.header,
      }
  
imports: import logging
  import torch
  from fate.arch import Context, dataframe
  from fate.ml.abc.module import HeteroModule
  from fate.ml.utils import predict_tools
  from fate.ml.utils._model_param import deserialize_param, initialize_param, serialize_param
  from fate.ml.utils._optimizer import LRScheduler, Optimizer
label_desc: Use image node_id 6 for calling the CoordinatedLinREstimatorGuest obj's underlying member method code with example usage: obj.get_model() and returns: dict