code: def _make_graph(self) -> None:
      for rank in range(self.world_size):
          for i in range(0, int(mlog(self.world_size - 1, 2)) + 1):
              f_peer = self._rotate_forward(rank, 2**i)
              b_peer = self._rotate_backward(rank, 2**i)
              self._add_peers(rank, [f_peer, b_peer])
  
imports: from abc import ABC, abstractmethod
  from math import log
  from typing import List, Optional, Tuple
  import torch
  import torch.distributed
label_desc: Use image node_id 1 for calling the DynamicDirectedExponentialGraph obj's underlying member method code with example usage: obj._make_graph() without return types