code: def test_precision_input_validation(xla_available):
      XLAPrecision(precision="32-true")
      XLAPrecision(precision="16-true")
      XLAPrecision(precision="bf16-true")
  
      with pytest.raises(
          ValueError,
          match=re.escape("`precision='16')` is not supported in XLA"),
      ):
          XLAPrecision("16")
      with pytest.raises(
          ValueError,
          match=re.escape(
              "`precision='16-mixed')` is not supported in XLA"
          ),
      ):
          XLAPrecision("16-mixed")
      with pytest.raises(
          ValueError,
          match=re.escape(
              "`precision='bf16-mixed')` is not supported in XLA"
          ),
      ):
          XLAPrecision("bf16-mixed")
      with pytest.raises(
          ValueError,
          match=re.escape(
              "`precision='64-true')` is not supported in XLA"
          ),
      ):
          XLAPrecision("64-true")
  
file_path: pytorch-lightning/tests/tests_fabric/plugins/precision/test_xla.py
imports: import os
  import re
  from unittest import mock
  import pytest
  import torch
  from lightning.fabric.plugins import XLAPrecision
label_desc: Use image node_id 1 for calling a global function with example usage: test_precision_input_validation(xla_available) without return types