code: def broadcast(
      self: torch.Tensor, src: int, group: RANK_TYPES, tag: str = ""
  ):
      """
      Broadcasts the tensor to all processes in the given process group.
  
      Args:
          src (int): Source rank
          group (ProcessGroup or List[int]): The process group to work on.
          tag (str, optional): A unique identifier for the collective. Default: empty string
      """
      tag, rankset, group_size = _expand_group(group, tag)
      tensor = torch.ops.c10d_functional.broadcast(
          self, src, tag, rankset, group_size
      )
      return _maybe_wrap_tensor(tensor)
  
imports: import sys
  import warnings
  from typing import cast, List, Optional, Tuple, TYPE_CHECKING, Union
  import torch
  import torch.distributed
  import torch.distributed.distributed_c10d
  from torch._custom_ops import impl_abstract
  from torch.distributed.device_mesh import DeviceMesh
  from torch.fx.experimental.proxy_tensor import get_innermost_proxy_mode
  from .None import _functional_collectives_impl
  from ._functional_collectives_impl import _register_tensor_wrapper
  from torch.distributed.distributed_c10d import all_gather_into_tensor, all_reduce, reduce_scatter_tensor
label_desc: Use image node_id 2 for calling a global function with example usage: broadcast(src, group, tag) and returns: _maybe_wrap_tensor