Implementations
Below are the agent implementations provided by torchelastic.
class torch.distributed.elastic.agent.server.local_elastic_agent.LocalElasticAgent(spec, start_method='spawn', exit_barrier_timeout=300, log_dir=None)
An implementation of "torchelastic.agent.server.ElasticAgent" that
   handles host-local workers. This agent is deployed per host and is
   configured to spawn "n" workers. When using GPUs, "n" maps to the
   number of GPUs available on the host.
The local agent does not communicate to other local agents deployed
   on other hosts, even if the workers may communicate inter-host. The
   worker id is interpreted to be a local process. The agent starts
   and stops all worker processes as a single unit.
The worker function and argument passed to the worker function must
   be python multiprocessing compatible. To pass multiprocessing data
   structures to the workers you may create the data structure in the