code: def __init__(
      self,
      epochs,
      batch_size,
      tol,
      early_stop,
      learning_rate,
      init_param,
      reveal_every_epoch=False,
      reveal_loss_freq=1,
      threshold=0.5,
  ):
      self.learning_rate = learning_rate
      self.epochs = epochs
      self.batch_size = batch_size
      self.tol = tol
      self.early_stop = early_stop
      self.learning_rate = learning_rate
      self.init_param = init_param
      self.threshold = threshold
      if reveal_every_epoch:
          raise ValueError(
              f"reveal_every_epoch is currenly not supported in SSHELogisticRegression"
          )
      self.reveal_every_epoch = reveal_every_epoch
      self.reveal_loss_freq = reveal_loss_freq
  
      self.estimator = None
      self.ovr = False
      self.labels = None
      self.label_count = None
  
imports: import logging
  import torch
  from fate.arch import Context, dataframe
  from fate.arch.dataframe import DataFrame
  from fate.arch.protocol.mpc.nn.sshe.lr_layer import SSHELogisticRegressionLayer, SSHELogisticRegressionLossLayer, 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 1 to create a new SSHELogisticRegression object from inherited base classes: Module with example: obj = SSHELogisticRegression(epochs, batch_size, tol, early_stop, learning_rate, init_param, reveal_every_epoch, reveal_loss_freq, threshold)