code: def _convert_sample_pos_to_weight(
      self, sample_pos: DataFrame, tree_nodes: List[Node]
  ):
      import functools
  
      map_func = functools.partial(
          _convert_sample_pos_to_score, tree_nodes=tree_nodes
      )
      sample_weight = sample_pos.apply_row(map_func, columns=["score"])
      return sample_weight
  
imports: import numpy
  import pandas
  from fate.arch import Context
  from fate.arch.dataframe import DataFrame
  from fate.ml.ensemble.learner.decision_tree.tree_core.splitter import SplitInfo
  from typing import List
  import logging
label_desc: Use image node_id 5 for calling the DecisionTree obj's underlying member method code with example usage: obj._convert_sample_pos_to_weight(sample_pos, tree_nodes) and returns: sample_weight