on both workers. Refer to "init_process_group()" API for more
      details. For example,
  export MASTER_ADDR=localhost export MASTER_PORT=5678

  Then run the following code in two different processes:

  >>> # On worker 0:
  >>> import torch
  >>> import torch.distributed.rpc as rpc
  >>> rpc.init_rpc("worker0", rank=0, world_size=2)
  >>> fut1 = rpc.rpc_async("worker1", torch.add, args=(torch.ones(2), 3))
  >>> fut2 = rpc.rpc_async("worker1", min, args=(1, 2))
  >>> result = fut1.wait() + fut2.wait()
  >>> rpc.shutdown()

  >>> # On worker 1:
  >>> import torch.distributed.rpc as rpc
  >>> rpc.init_rpc("worker1", rank=1, world_size=2)
  >>> rpc.shutdown()

  Below is an example of running a TorchScript function using RPC.

  >>> # On both workers:
  >>> @torch.jit.script
  >>> def my_script_add(t1, t2):
  >>>    return torch.add(t1, t2)

  >>> # On worker 0:
  >>> import torch.distributed.rpc as rpc
