code: def test_finetune_lr_schedulers(self):
      args_d: dict = CHEAP_ARGS.copy()
  
      task = "summarization"
      tmp_dir = make_test_data_dir(
          tmp_dir=self.get_auto_remove_tmp_dir()
      )
  
      model = BART_TINY
      output_dir = self.get_auto_remove_tmp_dir()
  
      args_d.update(
          data_dir=tmp_dir,
          model_name_or_path=model,
          output_dir=output_dir,
          tokenizer_name=None,
          train_batch_size=2,
          eval_batch_size=2,
          do_predict=False,
          task=task,
          src_lang="en_XX",
          tgt_lang="ro_RO",
          freeze_encoder=True,
          freeze_embeds=True,
      )
  
      # emulate finetune.py
      parser = argparse.ArgumentParser()
      parser = pl.Trainer.add_argparse_args(parser)
      parser = SummarizationModule.add_model_specific_args(
          parser, os.getcwd()
      )
      args = {"--help": True}
  
      # --help test
      with pytest.raises(SystemExit) as excinfo:
          with CaptureStdout() as cs:
              args = parser.parse_args(args)
          assert False, "--help is expected to sys.exit"
      assert excinfo.type == SystemExit
      expected = lightning_base.arg_to_scheduler_metavar
      assert (
          expected in cs.out
      ), "--help is expected to list the supported schedulers"
  
      # --lr_scheduler=non_existing_scheduler test
      unsupported_param = "non_existing_scheduler"
      args = {f"--lr_scheduler={unsupported_param}"}
      with pytest.raises(SystemExit) as excinfo:
          with CaptureStderr() as cs:
              args = parser.parse_args(args)
          assert False, "invalid argument is expected to sys.exit"
      assert excinfo.type == SystemExit
      expected = f"invalid choice: '{unsupported_param}'"
      assert (
          expected in cs.err
      ), f"should have bailed on invalid choice of scheduler {unsupported_param}"
  
      # --lr_scheduler=existing_scheduler test
      supported_param = "cosine"
      args_d1 = args_d.copy()
      args_d1["lr_scheduler"] = supported_param
      args = argparse.Namespace(**args_d1)
      model = main(args)
      assert (
          getattr(model.hparams, "lr_scheduler") == supported_param
      ), f"lr_scheduler={supported_param} shouldn't fail"
  
imports: import argparse
  import logging
  import os
  import sys
  import tempfile
  from pathlib import Path
  import pytest
  import pytorch_lightning
  import torch
  from torch import nn
  import lightning_base
  from convert_pl_checkpoint_to_hf import convert_pl_to_hf
  from distillation import distill_main
  from finetune import SummarizationModule, main
  from huggingface_hub import list_models
  from parameterized import parameterized
  from run_eval import generate_summaries_or_translations
  from transformers import AutoConfig, AutoModelForSeq2SeqLM
  from transformers.testing_utils import CaptureStderr, CaptureStdout, TestCasePlus, require_torch_gpu, slow
  from utils import label_smoothed_nll_loss, lmap, load_json
label_desc: Use image node_id 3 for calling the TestTheRest obj's underlying member method code with example usage: obj.test_finetune_lr_schedulers() without return types