81a34e895e1e657b8c41b631594cfcfda99f250d,basenji/seqnn.py,SeqNN,set_params,#SeqNN#Any#,478

Before Change

    if self.batch_renorm:
      RMAX_decay = ops.adjust_max(6000, 60000, 1, 3, name="RMAXDECAY")
      DMAX_decay = ops.adjust_max(6000, 60000, 0, 5, name="DMAXDECAY")
      self.renorm_clipping = {
          "rmin": 1. / RMAX_decay,
          "rmax": RMAX_decay,
          "dmax": DMAX_decay
      }
    else:
      self.renorm_clipping = {}

  def train_epoch(self,

After Change

    self.cnn_l2 = layer_extend(job.get("cnn_l2", []), 0, self.cnn_layers)

    self.final_l1 = job.get("final_l1", 0)
    self.batch_norm = bool(job.get("batch_norm", True))
    self.batch_renorm = bool(job.get("batch_renorm", False))
    self.batch_renorm = bool(job.get("renorm", self.batch_renorm))

    //////////////////////////////////////////////////////////////////////////////////////////////////////

Instances