class_docstr: Plugin for training with XLA.
  
  Args:
      precision: Full precision (32-true) or half precision (16-true, bf16-true).
  
  Raises:
      ValueError:
          If unsupported ``precision`` is provided.
code: def optimizer_step(
      self,
      optimizer: Optimizable,
      **kwargs: Any,
  ) -> Any:
      import torch_xla.core.xla_model as xm
  
      # you always want to `xm.mark_step()` after `optimizer.step` for better performance, so we set `barrier=True`
      return xm.optimizer_step(
          optimizer, optimizer_args=kwargs, barrier=True
      )
  
file_path: pytorch-lightning/src/lightning/fabric/plugins/precision/xla.py
imports: import os
  from typing import Any, Literal
  import torch
  from typing_extensions import get_args, override
  from lightning.fabric.accelerators.xla import _XLA_AVAILABLE
  from lightning.fabric.plugins.precision.precision import Precision
  from lightning.fabric.utilities.types import Optimizable
label_desc: Use image node_id 2 for calling the XLAPrecision obj's underlying member method code with example usage: obj.optimizer_step(optimizer) and returns: xm