code: def _sync_params_and_buffers(
      process_group: dist.ProcessGroup,
      module_states: List[torch.Tensor],
      broadcast_bucket_size: int,
      src: int,
  ) -> None:
      """Synchronize ``module_states`` (list of tensors) across all processes by broadcasting them from rank 0."""
      if len(module_states) > 0:
          dist._broadcast_coalesced(
              process_group, module_states, broadcast_bucket_size, src
          )
  
imports: import dataclasses
  import traceback
  from typing import Any, Callable, Container, Dict, List, Optional, OrderedDict, Tuple, TypeVar, overload
  import torch
  import torch.distributed
  from torch import nn
  from torch.nn.parallel._functions import _get_stream
  from torch.nn.parallel.scatter_gather import _is_namedtuple
  from torch.nn.utils.rnn import PackedSequence
label_desc: Use image node_id 16 for calling a global function with example usage: _sync_params_and_buffers(process_group, module_states, broadcast_bucket_size, src) without return types