code: def _make_graph(self) -> None:
      for rank in range(self.world_size):
          for i in range(
              0,
              int(mlog(self.world_size - 1, self._peers_per_itr + 1))
              + 1,
          ):
              for j in range(1, self._peers_per_itr + 1):
                  distance_to_neighbor = j * (
                      (self._peers_per_itr + 1) ** i
                  )
                  f_peer = self._rotate_forward(
                      rank, distance_to_neighbor
                  )
                  self._add_peers(rank, [f_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 NPeerDynamicDirectedExponentialGraph obj's underlying member method code with example usage: obj._make_graph() without return types