code: def test_1_optimizer_toggle_model():
      """Test toggle_model runs when only one optimizer is used."""
      model = BoringModel()
      trainer = Mock()
      model.trainer = trainer
      params = model.parameters()
      optimizer = torch.optim.SGD(params, lr=0.1)
      trainer.optimizers = [optimizer]
  
      assert not model._param_requires_grad_state
      # toggle optimizer was failing with a single optimizer
      model.toggle_optimizer(optimizer)
      assert model._param_requires_grad_state
      model.untoggle_optimizer(optimizer)
      assert not model._param_requires_grad_state
  
imports: import sys
  import weakref
  from unittest.mock import Mock
  import pytest
  import torch
  from lightning.fabric import Fabric
  from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_1_13, _TORCH_GREATER_EQUAL_2_0
  from lightning.pytorch import LightningModule, Trainer
  from lightning.pytorch.core.module import _TrainerFabricShim
  from lightning.pytorch.demos.boring_classes import BoringModel
  from lightning.pytorch.loggers import TensorBoardLogger
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from torch import nn
  from torch.optim import SGD, Adam
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 8 for calling a global function with example usage: test_1_optimizer_toggle_model() without return types