class_docstr: A light-weight wrapper class for torch.distributed API.
  Only a subset of functions are wrapped. Once the init_process_group
  is initialized, standard torch.distributed.* can be used directly
  so no need to wrap all the functions. We can keep adding wrappers as
  needed.
class_docstr_tok: ["A","light-weight","wrapper","class","for","torch.distributed","API",".","Only","a","subset","of","functions","are","wrapped",".","Once","the","init_process_group","is","initialized",",","standard","torch.distributed",".","*","can","be","used","directly","so","no","need","to","wrap","all","the","functions",".","We","can","keep","adding","wrappers","as","needed","."]
code: def barrier(
      self,
      group=torch.distributed.GroupMember.WORLD,
      async_op=False,
      device_ids=None,
  ):
      if group is None:
          group = torch.distributed.GroupMember.WORLD
      return torch.distributed.barrier(
          group=group, async_op=async_op, device_ids=device_ids
      )
  
imports: from deepspeed import utils
  from .utils import *
  from .backend import *
  from .comm import *
  import os
label_desc: Use image node_id 26 for calling the TorchBackend obj's underlying member method code with example usage: obj.barrier(group, async_op, device_ids) and returns: torch