code: def parity3d_checkpoint_syncbn_twice():
      rank = dist.get_rank()
      torch.cuda.set_device(rank)
      torch.manual_seed(rank)
  
      x = torch.randn(4, 3, 4, 4, 4).cuda() * rank
      torch_bn = torch.nn.SyncBatchNorm(3)
      torch_bn = nn.Sequential(torch_bn, torch_bn).cuda()
      fs_bn = SyncBatchNorm(3)
      fs_bn = nn.Sequential(fs_bn, fs_bn).cuda()
      fs_bn = checkpoint_wrapper(fs_bn)
      check_parity_ddp(torch_bn, fs_bn, x)
  
imports: import functools
  import tempfile
  import pytest
  import torch
  import torch.distributed
  import torch.multiprocessing
  import torch.nn
  from torch.nn.parallel import DistributedDataParallel
  from fairscale.experimental.nn import SyncBatchNorm
  from fairscale.nn.checkpoint import checkpoint_wrapper
label_desc: Use image node_id 9 for calling a global function with example usage: parity3d_checkpoint_syncbn_twice() without return types