code: def get_model(self):
      param = serialize_param(
          self.w, self.init_param.get("fit_intercept")
      )
      return {
          "param": param,
          # "optimizer": self.optimizer.state_dict(),
          "end_epoch": self.end_epoch,
          "is_converged": self.is_converged,
          "fit_intercept": self.init_param.get("fit_intercept"),
          "header": self.header,
          "lr": self.lr,
      }
  
imports: import logging
  import torch
  from fate.arch import Context, dataframe
  from fate.arch.dataframe import DataFrame
  from fate.arch.protocol.mpc.nn.sshe.linr_layer import SSHELinearRegressionLayer, SSHELinearRegressionLossLayer, SSHEOptimizerSGD
  from fate.ml.abc.module import Module, HeteroModule
  from fate.ml.utils import predict_tools
  from fate.ml.utils._convergence import converge_func_factory
  from fate.ml.utils._model_param import get_initialize_func
  from fate.ml.utils._model_param import serialize_param, deserialize_param
label_desc: Use image node_id 4 for calling the SSHELREstimator obj's underlying member method code with example usage: obj.get_model() and returns: dict