class_docstr: Strategy for training on a single XLA device.
class_docstr_tok: ["Strategy","for","training","on","a","single","XLA","device","."]
code: def precision(self, precision: Optional[XLAPrecision]) -> None:
      if precision is not None and not isinstance(
          precision, XLAPrecision
      ):
          raise TypeError(
              f"The XLA strategy can only work with the `XLAPrecision` plugin, found {precision}"
          )
      self._precision = precision
  
file_path: pytorch-lightning/src/lightning/fabric/strategies/single_xla.py
imports: from typing import Optional
  import torch
  from typing_extensions import override
  from lightning.fabric.accelerators import Accelerator
  from lightning.fabric.accelerators.xla import _XLA_AVAILABLE
  from lightning.fabric.plugins import XLAPrecision
  from lightning.fabric.plugins.io.xla import XLACheckpointIO
  from lightning.fabric.strategies import _StrategyRegistry
  from lightning.fabric.strategies.single_device import SingleDeviceStrategy
  from lightning.fabric.utilities.types import _DEVICE
label_desc: Use image node_id 5 for calling the SingleDeviceXLAStrategy obj's underlying member method code with example usage: obj.precision(precision) without return types