code: def _get_lrs(self, indices):
          
          if self.lr_scheduler is not None:
              lr = self.lr_scheduler(self.num_update)
          else:
              lr = self.lr
  
          lrs = [lr for _ in indices]
          for i, index in enumerate(indices):
              if index in self.param_dict:
                  lrs[i] *= self.param_dict[index].lr_mult
              elif index in self.lr_mult:
                  lrs[i] *= self.lr_mult[index]
              elif index in self.idx2name:
                  lrs[i] *= self.lr_mult.get(self.idx2name[index], 1.0)
          return lrs
docs: Gets the learning rates given the indices of the weights.
  
          Parameters
          ----------
          indices : list of int
              Indices corresponding to weights.
  
          Returns
          -------
          lrs : list of float
              Learning rates for those indices.