code: def restore(self, model):
      self.method = model["method"]
      self.bin_col = model["bin_col"]
      # self.transform_method = model["transform_method"]
      self._split_pt_dict = pd.DataFrame.from_dict(
          model["split_pt_dict"]
      )
      self._bin_idx_dict = model["bin_idx_dict"]
      self._bin_count_dict = model["bin_count_dict"]
      # load predict model
      if model.get("train_metrics_summary"):
          self._metrics_summary = model["metrics_summary"]
          self._train_metrics_summary = model["train_metrics_summary"]
      else:
          self._train_metrics_summary = model["metrics_summary"]
      if model.get("train_host_metrics_summary"):
          self._host_metrics_summary = model["host_metrics_summary"]
          self._train_host_metrics_summary = model[
              "train_host_metrics_summary"
          ]
      else:
          self._train_host_metrics_summary = model[
              "host_metrics_summary"
          ]
      if model.get("train_woe_dict"):
          self._woe_dict = model["woe_dict"]
          self._train_woe_dict = model["train_woe_dict"]
      else:
          self._train_woe_dict = model["woe_dict"]
  
      self.category_col = model["category_col"]
      self.adjustment_factor = model["adjustment_factor"]
  
imports: import logging
  import numpy
  import pandas
  from fate.arch import Context
  from fate.arch.histogram import HistogramBuilder
  from ..abc.module import HeteroModule, Module
label_desc: Use image node_id 9 for calling the StandardBinning obj's underlying member method code with example usage: obj.restore(model) without return types