Additional ones can be registered using the "register_backend()"
   function.
class torch.distributed.rpc.RpcBackendOptions
An abstract structure encapsulating the options passed into the RPC
   backend. An instance of this class can be passed in to "init_rpc()"
   in order to initialize RPC with specific configurations, such as
   the RPC timeout and "init_method" to be used.
property init_method
  URL specifying how to initialize the process group. Default is
  "env://"

property rpc_timeout
  A float indicating the timeout to use for all RPCs. If an RPC
  does not complete in this timeframe, it will complete with an
  exception indicating that it has timed out.

TensorPipe Backend
~~~~~~~~~~~~~~~~~~
The TensorPipe agent, which is the default, leverages the TensorPipe
library, which provides a natively point-to-point communication
primitive specifically suited for machine learning that fundamentally
addresses some of the limitations of Gloo. Compared to Gloo, it has