class_docstr: Static rendezvous that is a wrapper around the TCPStore.
  
  Creates TCPStore based on the input parameters with the
  listener on the agent with group_rank=0
class_docstr_tok: ["Static","rendezvous","that","is","a","wrapper","around","the","TCPStore",".","Creates","TCPStore","based","on","the","input","parameters","with","the","listener","on","the","agent","with","group_rank=0"]
code: def __init__(
      self,
      master_addr: str,
      master_port: int,
      rank: int,
      world_size: int,
      run_id: str,
      timeout: int,
  ):
      self.master_addr = master_addr
      self.master_port = master_port
      self.rank = rank
      self.world_size = world_size
      self.run_id = run_id
      self.timeout = datetime.timedelta(seconds=timeout)
      self._store: Optional[Store] = None
  
file_path: pytorch/torch/distributed/elastic/rendezvous/static_tcp_rendezvous.py
imports: import datetime
  import logging
  from typing import Tuple, cast, Optional
  from torch.distributed import Store, TCPStore, PrefixStore
  from torch.distributed.elastic.rendezvous import RendezvousHandler, RendezvousParameters
  from torch.distributed.elastic.rendezvous.utils import parse_rendezvous_endpoint
label_desc: Use image node_id 1 to create a new StaticTCPRendezvous object from inherited base classes: RendezvousHandler with example: obj = StaticTCPRendezvous(master_addr, master_port, rank, world_size, run_id, timeout)