code: def test_auto_scale_batch_size_with_amp(tmpdir):
      before_batch_size = 2
      model = BatchSizeModel(batch_size=before_batch_size)
      trainer = Trainer(
          default_root_dir=tmpdir,
          max_steps=1,
          accelerator="gpu",
          devices=1,
          precision="16-mixed",
      )
      tuner = Tuner(trainer)
      tuner.scale_batch_size(model)
      after_batch_size = model.batch_size
      assert trainer.scaler is not None
      assert after_batch_size != before_batch_size
  
imports: import logging
  import os
  from copy import deepcopy
  from unittest.mock import patch
  import pytest
  import torch
  from lightning.pytorch import Trainer
  from lightning.pytorch.callbacks.batch_size_finder import BatchSizeFinder
  from lightning.pytorch.demos.boring_classes import BoringDataModule, BoringModel, RandomDataset
  from lightning.pytorch.tuner.tuning import Tuner
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from lightning_utilities.test.warning import no_warning_call
  from torch.utils.data import DataLoader
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 9 for calling a global function with example usage: test_auto_scale_batch_size_with_amp(tmpdir) without return types