code: def test_init_optimizers_during_evaluation_and_prediction(tmpdir, fn):
      """Test that optimizers is an empty list during evaluation and prediction."""
  
      class TestModel(BoringModel):
          def configure_optimizers(self):
              optimizer1 = optim.Adam(self.parameters(), lr=0.1)
              optimizer2 = optim.Adam(self.parameters(), lr=0.1)
              lr_scheduler1 = optim.lr_scheduler.StepLR(
                  optimizer1, step_size=1
              )
              lr_scheduler2 = optim.lr_scheduler.StepLR(
                  optimizer2, step_size=1
              )
              return [optimizer1, optimizer2], [
                  lr_scheduler1,
                  lr_scheduler2,
              ]
  
      trainer = Trainer(default_root_dir=tmpdir, fast_dev_run=2)
      train_fn = getattr(trainer, fn)
      train_fn(
          TestModel(), datamodule=BoringDataModule(), ckpt_path=None
      )
  
      assert len(trainer.lr_scheduler_configs) == 0
      assert len(trainer.optimizers) == 0
  
imports: from unittest import mock
  from unittest.mock import call
  import pytest
  import torch
  from lightning.pytorch import Trainer
  from lightning.pytorch.callbacks import ModelCheckpoint
  from lightning.pytorch.core.optimizer import _configure_optimizers, _configure_schedulers_automatic_opt, _init_optimizers_and_lr_schedulers
  from lightning.pytorch.demos.boring_classes import BoringDataModule, BoringModel
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from lightning.pytorch.utilities.types import LRSchedulerConfig
  from torch import optim
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 11 for calling a global function with example usage: test_init_optimizers_during_evaluation_and_prediction(tmpdir, fn) and returns: list,  list