code: def node_gain(self, g, h):
      g, h = self.truncate(g), self.truncate(h)
      g = self._l1_reg(g)
      if isinstance(h, np.ndarray):
          h[h == 0] = np.nan
      score = (g * g) / (h + self.l2)
      return score
  
imports: import torch
  import numpy
  import logging
  from fate.arch.dataframe import DataFrame
  from fate.arch import Context
  from fate.arch.histogram import DistributedHistogram
label_desc: Use image node_id 5 for calling the SBTSplitter obj's underlying member method code with example usage: obj.node_gain(g, h) and returns: score