code: def test_step_shape(self):
      kwargs = dict(self.forward_default_kwargs)
  
      num_inference_steps = kwargs.pop("num_inference_steps", None)
  
      timestep_0 = 1
      timestep_1 = 0
  
      for scheduler_class in self.scheduler_classes:
          if scheduler_class in (
              EulerAncestralDiscreteScheduler,
              EulerDiscreteScheduler,
              LMSDiscreteScheduler,
          ):
              timestep_0 = float(timestep_0)
              timestep_1 = float(timestep_1)
  
          scheduler_config = self.get_scheduler_config()
          scheduler = scheduler_class(**scheduler_config)
  
          if scheduler_class == VQDiffusionScheduler:
              num_vec_classes = scheduler_config["num_vec_classes"]
              sample = self.dummy_sample(num_vec_classes)
              model = self.dummy_model(num_vec_classes)
              residual = model(sample, timestep_0)
          else:
              sample = self.dummy_sample
              residual = 0.1 * sample
  
          if num_inference_steps is not None and hasattr(
              scheduler, "set_timesteps"
          ):
              scheduler.set_timesteps(num_inference_steps)
          elif num_inference_steps is not None and not hasattr(
              scheduler, "set_timesteps"
          ):
              kwargs["num_inference_steps"] = num_inference_steps
  
          output_0 = scheduler.step(
              residual, timestep_0, sample, **kwargs
          ).prev_sample
          output_1 = scheduler.step(
              residual, timestep_1, sample, **kwargs
          ).prev_sample
  
          self.assertEqual(output_0.shape, sample.shape)
          self.assertEqual(output_0.shape, output_1.shape)
  
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 11 for calling the SchedulerCommonTest obj's underlying member method code with example usage: obj.test_step_shape() without return types