code: def _distribute_region(self, spec: DTensorSpec):
      # check if the tensor parallel rng state has been synchronized or not
      if not self.rng_state_is_sync("tensor-parallel-rng"):
          raise RuntimeError(
              "TensorParallelRNGTracker requires the random state to be synchronized "
              "before entering into a distribute region!"
          )
  
      if self.distribute_region_enabled:
          with torch.random.fork_rng(
              self._devices, device_type=self._device_type
          ):
              self._device_handle.set_rng_state(
                  self.rng_states["tensor-parallel-rng"]
              )
              try:
                  yield
              finally:
                  self.rng_states[
                      "tensor-parallel-rng"
                  ] = self._device_handle.get_rng_state()
      else:
          yield
  
imports: import contextlib
  import warnings
  from typing import Dict, List, Optional
  import torch
  import torch.distributed
  from torch import Tensor
  from torch.distributed._tensor.placement_types import DTensorSpec, Shard
  from torch.distributed.device_mesh import _get_device_handle, DeviceMesh
label_desc: Use image node_id 3 for calling the TensorParallelRNGTracker obj's underlying member method code with example usage: obj._distribute_region(spec) without return types