code: def test_pipeline_different_schedulers(self):
      pipeline = self.pipeline_class(**self.get_dummy_components())
      inputs = self.get_dummy_inputs("cpu")
  
      expected_image_size = (16, 16, 3)
      for scheduler_cls in [
          DDIMScheduler,
          DEISMultistepScheduler,
          DPMSolverMultistepScheduler,
      ]:
          pipeline.scheduler = scheduler_cls.from_config(
              pipeline.scheduler.config
          )
          image = pipeline(**inputs).images[0]
  
          shape = image.shape
          assert shape == expected_image_size
  
      pipeline.scheduler = EulerDiscreteScheduler.from_config(
          pipeline.scheduler.config
      )
  
      with self.assertRaises(ValueError):
          # Karras schedulers are not supported
          image = pipeline(**inputs).images[0]
  
imports: import gc
  import unittest
  import numpy
  import torch
  from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
  from diffusers import AutoencoderKL, DDIMScheduler, DEISMultistepScheduler, DPMSolverMultistepScheduler, EulerDiscreteScheduler, StableDiffusionSAGPipeline, UNet2DConditionModel
  from diffusers.utils.testing_utils import enable_full_determinism, nightly, require_torch_gpu, torch_device
  from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_IMAGE_PARAMS, TEXT_TO_IMAGE_PARAMS
  from ..test_pipelines_common import PipelineLatentTesterMixin, PipelineTesterMixin
label_desc: Use image node_id 5 for calling the StableDiffusionSAGPipelineFastTests obj's underlying member method code with example usage: obj.test_pipeline_different_schedulers() without return types