code: def test_transformer_engine_precision_plugin(monkeypatch):
      module = lightning.fabric.plugins.precision.transformer_engine
      if module._TRANSFORMER_ENGINE_AVAILABLE:
          pytest.skip("Assumes transformer_engine is unavailable")
      monkeypatch.setattr(
          module, "_TRANSFORMER_ENGINE_AVAILABLE", lambda: True
      )
      monkeypatch.setitem(sys.modules, "transformer_engine", Mock())
      monkeypatch.setitem(
          sys.modules, "transformer_engine.common.recipe", Mock()
      )
  
      connector = _AcceleratorConnector(precision="transformer-engine")
      assert isinstance(
          connector.precision_plugin, TransformerEnginePrecision
      )
      assert connector.precision_plugin.weights_dtype is torch.bfloat16
      connector = _AcceleratorConnector(
          precision="transformer-engine-float16"
      )
      assert connector.precision_plugin.weights_dtype is torch.float16
  
      precision = TransformerEnginePrecision(
          weights_dtype=torch.float32
      )
      connector = _AcceleratorConnector(plugins=precision)
      assert connector.precision_plugin is precision
  
file_path: pytorch-lightning/tests/tests_pytorch/plugins/precision/test_transformer_engine.py
imports: import sys
  from contextlib import nullcontext
  from unittest.mock import ANY, Mock
  import lightning.fabric
  import pytest
  import torch
  from lightning.pytorch import LightningModule, Trainer
  from lightning.pytorch.plugins import TransformerEnginePrecision
  from lightning.pytorch.trainer.connectors.accelerator_connector import _AcceleratorConnector
label_desc: Use image node_id 1 for calling a global function with example usage: test_transformer_engine_precision_plugin(monkeypatch) without return types