code: def test_unsupported_manual_optimization():
      """Test that an error is raised when attempting to use the callback with manual optimization."""
      scheduler = GradientAccumulationScheduler({1: 2})
      model = BoringModel()
      model.automatic_optimization = False
      trainer = Trainer()
      with pytest.raises(
          RuntimeError,
          match="Automatic gradient accumulation and the `GradientAccumulationScheduler`",
      ):
          scheduler.on_train_start(trainer, model)
  
file_path: pytorch-lightning/tests/tests_pytorch/callbacks/test_gradient_accumulation_scheduler.py
imports: import math
  from unittest.mock import Mock, patch
  import pytest
  from lightning.pytorch import Trainer
  from lightning.pytorch.callbacks import GradientAccumulationScheduler
  from lightning.pytorch.demos.boring_classes import BoringModel
  from lightning.pytorch.strategies import DeepSpeedStrategy
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from lightning.pytorch.utilities.imports import _LIGHTNING_COLOSSALAI_AVAILABLE
label_desc: Use image node_id 6 for calling a global function with example usage: test_unsupported_manual_optimization() without return types