(running on processes on the same host).
class torch.distributed.elastic.timer.LocalTimerClient(mp_queue)
Client side of "LocalTimerServer". This client is meant to be used
   on the same host that the "LocalTimerServer" is running on and uses
   pid to uniquely identify a worker. This is particularly useful in
   situations where one spawns a subprocess (trainer) per GPU on a
   host with multiple GPU devices.
Below is another pair of timer server and client that is implemented
based on a named pipe.
class torch.distributed.elastic.timer.FileTimerServer(file_path, max_interval=10, daemon=True, log_event=None)
Server that works with "FileTimerClient". Clients are expected to
   be running on the same host as the process that is running this
   server. Each host in the job is expected to start its own timer
   server locally and each server instance manages timers for local
   workers (running on processes on the same host).
Parameters: