code: def skip_synchronize(self):
      if self._enable_async:
          raise AssertionError(
              "skip_synchronize cannot be used in async training"
          )
      self._should_sync = False
      try:
          yield
      finally:
          self._should_sync = True
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from contextlib import contextmanager
  from byteps.torch.compression import Compression
  from byteps.torch.ops import push_pull_async_inplace
  from byteps.torch.ops import push_pull
  from byteps.torch.ops import poll, synchronize, declare
  from byteps.torch.ops import init, shutdown, suspend, resume
  from byteps.torch.ops import size, local_size, rank, local_rank
  import os
  import torch
  import collections
  import io
  import cloudpickle
label_desc: Use image node_id 8 for calling the _DistributedOptimizer obj's underlying member method code with example usage: obj.skip_synchronize() without return types