code: def backend() -> Optional[str]:
      """Returns computation model's backend.
  
      - `None` for no distributed configuration
      - "nccl" or "gloo" or "mpi" for native torch distributed configuration
      - "xla-tpu" for XLA distributed configuration
      - "horovod" for Horovod distributed framework
  
      Returns:
          str or None
  
      .. versionchanged:: 0.4.2
          Added Horovod distributed framework.
      """
      if _need_to_sync and isinstance(_model, _SerialModel):
          sync(temporary=True)
  
      return _model.backend()
  
imports: import socket
  from contextlib import contextmanager
  from functools import wraps
  from typing import Any, Callable, List, Mapping, Optional, Tuple, Union
  import torch
  from ignite.distributed.comp_models import _SerialModel, has_hvd_support, has_native_dist_support, has_xla_support, registered_computation_models
  from ignite.utils import setup_logger
label_desc: Use image node_id 3 for calling a global function with example usage: backend() and returns: _model