code: def apply_flat_dist_call(bucket, call, extra_args=None):
      coalesced = flatten(bucket)
  
      if extra_args is not None:
          call(coalesced, *extra_args)
      else:
          call(coalesced)
  
      if call is dist.all_reduce:
          coalesced /= dist.get_world_size()
  
      for buf, synced in zip(bucket, unflatten(coalesced, bucket)):
          buf.copy_(synced)
  
imports: from collections import OrderedDict
  import copy
  import importlib
  from itertools import chain
  import torch
  import torch.distributed
  from torch.nn.modules import Module
  from torch.autograd import Variable
  from ..multi_tensor_apply import multi_tensor_applier
label_desc: Use image node_id 4 for calling a global function with example usage: apply_flat_dist_call(bucket, call, extra_args) without return types