code: def patch_replication_callback(data_parallel):
      """
      Monkey-patch an existing `DataParallel` object. Add the replication callback.
      Useful when you have customized `DataParallel` implementation.
  
      Examples:
          > sync_bn = SynchronizedBatchNorm1d(10, eps=1e-5, affine=False)
          > sync_bn = DataParallel(sync_bn, device_ids=[0, 1])
          > patch_replication_callback(sync_bn)
          # this is equivalent to
          > sync_bn = SynchronizedBatchNorm1d(10, eps=1e-5, affine=False)
          > sync_bn = DataParallelWithCallback(sync_bn, device_ids=[0, 1])
      """
  
      assert isinstance(data_parallel, DataParallel)
  
      old_replicate = data_parallel.replicate
  
      @functools.wraps(old_replicate)
      def new_replicate(module, device_ids):
          modules = old_replicate(module, device_ids)
          execute_replication_callbacks(modules)
          return modules
  
      data_parallel.replicate = new_replicate
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  import threading
  import torch
  import torch.cuda.comm
  from torch.autograd import Variable, Function
  from torch.nn.parallel.data_parallel import DataParallel
  from torch.nn.parallel.parallel_apply import get_a_var
  from torch.nn.parallel._functions import ReduceAddCoalesced, Broadcast
label_desc: Use image node_id 4 for calling a global function with example usage: patch_replication_callback(data_parallel) and returns: modules