code: def __init__(
      self,
      epochs=None,
      early_stop=None,
      tol=None,
      batch_size=None,
      optimizer=None,
      learning_rate_scheduler=None,
  ):
      self.epochs = epochs
      self.batch_size = batch_size
      self.early_stop = early_stop
      self.tol = tol
      self.optimizer = optimizer
      self.lr_scheduler = learning_rate_scheduler
  
      if early_stop is not None:
          self.converge_func = converge_func_factory(early_stop, tol)
      self.start_epoch = 0
      self.end_epoch = -1
      self.is_converged = False
  
imports: import logging
  import torch
  from fate.arch import Context
  from fate.arch.dataframe import DataLoader
  from fate.ml.abc.module import HeteroModule
  from fate.ml.utils._convergence import converge_func_factory
  from fate.ml.utils._optimizer import LRScheduler, Optimizer, separate
label_desc: Use image node_id 1 to create a new HeteroLinREstimatorArbiter object from inherited base classes: HeteroModule with example: obj = HeteroLinREstimatorArbiter(epochs, early_stop, tol, batch_size, optimizer, learning_rate_scheduler)