code: def _l1_reg(self, g):
      if self.l1 == 0:
          return g
      if isinstance(g, torch.Tensor):
          g[g < -self.l1] += self.l1
          g[g > self.l1] -= self.l1
          g[(g <= self.l1) & (g >= -self.l1)] = 0
      else:
          if g < -self.l1:
              return g + self.l1
          elif g > self.l1:
              return g - self.l1
          else:
              return 0
      return g
  
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 4 for calling the SBTSplitter obj's underlying member method code with example usage: obj._l1_reg(g) and returns: g, g, unknown, unknown, int