code: def test_from_pretrained(self):
      for scheduler_class in self.scheduler_classes:
          scheduler_config = self.get_scheduler_config()
  
          scheduler = scheduler_class(**scheduler_config)
  
          with tempfile.TemporaryDirectory() as tmpdirname:
              scheduler.save_pretrained(tmpdirname)
              new_scheduler = scheduler_class.from_pretrained(
                  tmpdirname
              )
  
          # `_use_default_values` should not exist for just saved & loaded scheduler
          scheduler_config = dict(scheduler.config)
          del scheduler_config["_use_default_values"]
  
          assert scheduler_config == new_scheduler.config
  
imports: import inspect
  import json
  import os
  import tempfile
  import unittest
  import uuid
  from typing import Dict, List, Tuple
  import numpy
  import torch
  from huggingface_hub import delete_repo
  import diffusers
  from diffusers import CMStochasticIterativeScheduler, DDIMScheduler, DEISMultistepScheduler, DiffusionPipeline, EulerAncestralDiscreteScheduler, EulerDiscreteScheduler, IPNDMScheduler, LMSDiscreteScheduler, UniPCMultistepScheduler, VQDiffusionScheduler, logging
  from diffusers.configuration_utils import ConfigMixin, register_to_config
  from diffusers.schedulers.scheduling_utils import SchedulerMixin
  from diffusers.utils.testing_utils import CaptureLogger, torch_device
  from ..others.test_utils import TOKEN, USER, is_staging_test
label_desc: Use image node_id 10 for calling the SchedulerCommonTest obj's underlying member method code with example usage: obj.test_from_pretrained() without return types