class_docstr: Synchronize model buffers such as running_mean and running_var in BN at
  the end of each epoch.
  
  Args:
      distributed (bool): Whether distributed training is used. It is
        effective only for distributed training. Defaults to True.
class_docstr_tok: ["Synchronize","model","buffers","such","as","running_mean","and","running_var","in","BN","at","the","end","of","each","epoch",".","Args",":","distributed","(","bool",")",":","Whether","distributed","training","is","used",".","It","is","effective","only","for","distributed","training",".","Defaults","to","True","."]
code: def __init__(self, distributed=True):
      self.distributed = distributed
  
imports: from ..dist_utils import allreduce_params
  from .hook import HOOKS, Hook
label_desc: Use image node_id 1 to create a new SyncBuffersHook object from inherited base classes: Hook with example: obj = SyncBuffersHook(distributed)