class_docstr: Launches processes that run a given function in parallel on XLA supported hardware, and joins them all at the
  end.
  
  The main process in which this launcher is invoked creates N so-called worker processes (using the
  `torch_xla` :func:`xmp.spawn`) that run the given function.
  Worker processes have a rank that ranges from 0 to N - 1.
  
  Note:
      - This launcher requires all objects to be pickleable.
      - It is important that the entry point to the program/script is guarded by ``if __name__ == "__main__"``.
  
  Args:
      strategy: A reference to the strategy that is used together with this launcher
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code: def is_interactive_compatible(self) -> bool:
      return True
  
file_path: pytorch-lightning/src/lightning/pytorch/strategies/launchers/xla.py
imports: import os
  import queue
  from typing import TYPE_CHECKING, Any, Callable, Optional, Union
  import torch.multiprocessing
  from typing_extensions import override
  from lightning.fabric.accelerators.xla import _XLA_AVAILABLE
  from lightning.fabric.strategies.launchers.xla import _rank_teardown
  from lightning.fabric.utilities import move_data_to_device
  from lightning.pytorch.strategies.launchers.multiprocessing import _GlobalStateSnapshot, _MultiProcessingLauncher, _WorkerOutput
  from lightning.pytorch.trainer.states import TrainerFn
  from lightning.pytorch.utilities.rank_zero import rank_zero_debug
label_desc: Use image node_id 2 for calling the _XLALauncher obj's underlying member method code with example usage: obj.is_interactive_compatible() and returns: True