code: def SyncBatchNorm(*args, **kwargs):
      """In cpu environment nn.SyncBatchNorm does not have kernel so use nn.BatchNorm2D instead"""
      if (
          paddle.get_device() == "cpu"
          or os.environ.get("PADDLESEG_EXPORT_STAGE")
          or "xpu" in paddle.get_device()
          or "npu" in paddle.get_device()
      ):
          return nn.BatchNorm2D(*args, **kwargs)
      elif paddle.distributed.ParallelEnv().nranks == 1:
          return nn.BatchNorm2D(*args, **kwargs)
      else:
          return nn.SyncBatchNorm(*args, **kwargs)
  
imports: import os
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.models import layers
label_desc: Use image node_id 1 for calling a global function with example usage: SyncBatchNorm() and returns: nn, nn, nn