code: def _prepare_hist_sub(
      self,
      nodes: List[Node],
      cur_layer_node_map: dict,
      parent_node_map: dict,
  ):
      weak_nodes_ids = []
      mapping = []
      n_map = {n.nid: n for n in nodes}
      new_node_map = {}
      hist_pos = 0
      for n in nodes:
          if n.nid == 0:
              # root node
              weak_nodes_ids.append(0)
              # root node, just return
              return set(weak_nodes_ids), None, mapping
  
          if n.is_left_node:
              sib = n_map[n.sibling_nodeid]
  
              if sib.sample_num < n.sample_num:
                  weak_node = sib
              else:
                  weak_node = n
  
              mapping_list = []
              parent_nid = weak_node.parent_nodeid
              weak_nodes_ids.append(weak_node.nid)
              mapping_list = (
                  parent_node_map[parent_nid],
                  hist_pos,
                  cur_layer_node_map[weak_node.nid],
                  cur_layer_node_map[weak_node.sibling_nodeid],
              )
              mapping.append(mapping_list)
              new_node_map[weak_node.nid] = hist_pos
              hist_pos += 1
  
          else:
              continue
      return set(weak_nodes_ids), new_node_map, mapping
  
imports: import typing
  import torch
  from typing import Dict
  from fate.arch.histogram import HistogramBuilder, DistributedHistogram
  from fate.ml.ensemble.learner.decision_tree.tree_core.decision_tree import Node
  from typing import List
  import numpy
  from fate.arch.dataframe import DataFrame
  from fate.arch import Context
  import logging
label_desc: Use image node_id 5 for calling the SBTHistogramBuilder obj's underlying member method code with example usage: obj._prepare_hist_sub(nodes, cur_layer_node_map, parent_node_map) and returns: set,  new_node_map,  mapping, set,  None,  mapping