code: def __init__(
      self,
      rank: int,
      world_size: int,
      nprocs_per_node: int = 1,
      local_rank: int = 0,
      peers_per_itr: int = 1,
  ) -> None:
      assert int(peers_per_itr) >= 1
      self.rank = rank
      self.world_size = world_size
      self.phone_book: List[List[Edge]] = [
          [] for _ in range(self.world_size)
      ]
      self._peers_per_itr = peers_per_itr
      self._group_indices = list(range(peers_per_itr))
      self.nprocs_per_node = nprocs_per_node
      self.local_rank = local_rank
      self._make_graph()
  
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 to create a new GraphManager object from inherited base classes: ABC with example: obj = GraphManager(rank, world_size, nprocs_per_node, local_rank, peers_per_itr)