class_docstr: Strategy for training multiple TPU devices using the :func:`torch_xla.distributed.xla_multiprocessing.spawn`
  method.
code: def broadcast(self, obj: TBroadcast, src: int = 0) -> TBroadcast:
      if not self._launched:
          return obj
  
      import torch_xla.core.xla_model as xm
  
      is_tensor = isinstance(obj, Tensor)
      if is_tensor:
          if obj.dim() == 0:
              obj = obj.unsqueeze(0)
          original_device = obj.device
          # XLA distributed requires that the data is on the XLA device
          obj = obj.to(self.root_device)
      else:
          # support for arbitrary pickle-ables
          buffer = io.BytesIO()
          torch.save(obj, buffer)
          obj = torch.tensor(  # type: ignore[assignment]
              bytearray(buffer.getbuffer()),
              device=self.root_device,
              dtype=torch.float,
          )
  
      obj = [obj]
      xm.collective_broadcast(obj, root_ordinal=src)
      obj = obj[0]
  
      if not is_tensor:
          # this will preserve the dtype and device of any tensors
          buffer = io.BytesIO(obj.cpu().byte().numpy())
          obj = torch.load(buffer)
      else:
          obj = obj.to(original_device)
  
      return obj
  
imports: import io
  from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Union
  import torch
  from torch import Tensor
  from torch.nn import Module
  from torch.optim import Optimizer
  from torch.utils.data import DataLoader
  from typing_extensions import override
  from lightning.fabric.accelerators import Accelerator
  from lightning.fabric.accelerators.xla import _XLA_GREATER_EQUAL_2_1
  from lightning.fabric.plugins import XLAPrecision
  from lightning.fabric.plugins.environments import XLAEnvironment
  from lightning.fabric.plugins.io.xla import XLACheckpointIO
  from lightning.fabric.strategies import ParallelStrategy, _StrategyRegistry
  from lightning.fabric.strategies.launchers.xla import _XLALauncher
  from lightning.fabric.strategies.strategy import TBroadcast
  from lightning.fabric.utilities.rank_zero import rank_zero_only
  from lightning.fabric.utilities.types import _PATH, ReduceOp
label_desc: Use image node_id 20 for calling the XLAStrategy obj's underlying member method code with example usage: obj.broadcast(obj, src) and returns: obj, obj