code: def synchronize():
      """
      Helper function to synchronize (barrier) among all processes when
      using distributed training
      """
      if not dist.is_available():
          return
      if not dist.is_initialized():
          return
      world_size = dist.get_world_size()
      if world_size == 1:
          return
      dist.barrier()
  
imports: import functools
  import logging
  import pickle
  import torch
  import torch.distributed
  from pytorchvideo.layers.distributed import cat_all_gather, get_local_process_group, get_local_rank, get_local_size, get_world_size, init_distributed_training
label_desc: Use image node_id 8 for calling a global function with example usage: synchronize() without return types