code: def get_ray_trainer_backend(
      cls, nics: Optional[List[str]] = None, **kwargs
  ) -> Optional[Any]:
      from ray.train.horovod import HorovodConfig
  
      # Explicitly override network interfaces Horovod will attempt to use
      if nics is not None:
          nics = set(nics)
      return HorovodConfig(nics=nics)
  
imports: import contextlib
  import logging
  from typing import Any, Callable, Dict, List, Optional, Tuple, Type, TYPE_CHECKING
  import horovod.torch
  import ray
  import torch
  from horovod.torch.optimizer import _DistributedOptimizer
  from packaging import version
  from ray.train.backend import BackendConfig
  from ray.train.data_parallel_trainer import DataParallelTrainer
  from ray.train.horovod import HorovodTrainer
  from torch import nn
  from torch.optim import Optimizer
  from ludwig.constants import AUTO
  from ludwig.distributed.base import DistributedStrategy
  from ludwig.modules.optimization_modules import create_optimizer
  from ludwig.utils.horovod_utils import gather_all_tensors, is_distributed_available
label_desc: Use image node_id 18 for calling the HorovodStrategy obj's underlying member method code with example usage: obj.get_ray_trainer_backend(cls, nics) and returns: HorovodConfig