class_docstr: Strategy for training on a single XLA device.
code: def setup(self, trainer: "pl.Trainer") -> None:
      assert (
          self.model
      ), "self.model must be set before find_shared_parameters(self.model)"
      shared_params = find_shared_parameters(self.model)
      self.model_to_device()
      set_shared_parameters(self.model, shared_params)
      super().setup(trainer)
  
      if self.debug:
          os.environ["PT_XLA_DEBUG"] = str(1)
  
imports: import os
  from typing import Optional, Union
  import torch
  from typing_extensions import override
  import lightning.pytorch
  from lightning.fabric.accelerators.xla import _XLA_AVAILABLE
  from lightning.fabric.plugins import XLACheckpointIO
  from lightning.fabric.strategies import _StrategyRegistry
  from lightning.fabric.utilities.types import _DEVICE
  from lightning.pytorch.plugins.io.wrapper import _WrappingCheckpointIO
  from lightning.pytorch.plugins.precision.xla import XLAPrecision
  from lightning.pytorch.strategies.single_device import SingleDeviceStrategy
  from lightning.pytorch.utilities import find_shared_parameters, set_shared_parameters
label_desc: Use image node_id 6 for calling the SingleDeviceXLAStrategy obj's underlying member method code with example usage: obj.setup(trainer) without return types