code: def main(
      num_workers,
      use_gpu,
      timeout_s=30,
      placement_group_timeout_s=100,
      kwargs=None,
  ):
      kwargs = kwargs or {}
      if use_gpu:
          kwargs["use_cuda"] = True
      settings = RayExecutor.create_settings(
          timeout_s=timeout_s,
          placement_group_timeout_s=placement_group_timeout_s,
      )
      executor = RayExecutor(
          settings, use_gpu=use_gpu, num_workers=num_workers
      )
      executor.start()
      executor.run(train_fn, kwargs=kwargs)
  
file_path: ray/python/ray/tests/horovod/horovod_example.py
imports: import argparse
  import os
  from filelock import FileLock
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from torchvision import datasets, transforms
  import torch.utils.data.distributed
  import horovod.torch
  from horovod.ray import RayExecutor
label_desc: Use image node_id 3 for calling a global function with example usage: main(num_workers, use_gpu, timeout_s, placement_group_timeout_s, kwargs) without return types