else:
             print(f"worker 0 return value is: run_result.return_values[0]")
     except Exception ex:
         # handle exception
Rendezvous Handler
To implement your own rendezvous, extend
"torch.distributed.elastic.rendezvous.RendezvousHandler" and implement
its methods.
Warning:
Rendezvous handlers are tricky to implement. Before you begin make
  sure you completely understand the properties of rendezvous. Please
  refer to Rendezvous for more information.
Once implemented you can pass your custom rendezvous handler to the
worker spec when creating the agent.
spec = WorkerSpec(
       rdzv_handler=MyRendezvousHandler(params),
       ...
   )
   elastic_agent = LocalElasticAgent(spec, start_method=start_method)
   elastic_agent.run(spec.role)
Metric Handler
TorchElastic emits platform level metrics (see Metrics). By default
metrics are emitted to /dev/null so you will not see them. To have