code: def test_stable_diffusion_model_editing_pipeline_with_sequential_cpu_offloading(
      self,
  ):
      torch.cuda.empty_cache()
      torch.cuda.reset_max_memory_allocated()
      torch.cuda.reset_peak_memory_stats()
  
      model_ckpt = "CompVis/stable-diffusion-v1-4"
      scheduler = DDIMScheduler.from_pretrained(
          model_ckpt, subfolder="scheduler"
      )
      pipe = StableDiffusionModelEditingPipeline.from_pretrained(
          model_ckpt, scheduler=scheduler, safety_checker=None
      )
      pipe = pipe.to(torch_device)
      pipe.set_progress_bar_config(disable=None)
      pipe.enable_attention_slicing(1)
      pipe.enable_sequential_cpu_offload()
  
      inputs = self.get_inputs()
      _ = pipe(**inputs)
  
      mem_bytes = torch.cuda.max_memory_allocated()
      # make sure that less than 4.4 GB is allocated
      assert mem_bytes < 4.4 * 10**9
  
imports: import gc
  import unittest
  import numpy
  import torch
  from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
  from diffusers import AutoencoderKL, DDIMScheduler, EulerAncestralDiscreteScheduler, PNDMScheduler, StableDiffusionModelEditingPipeline, UNet2DConditionModel
  from diffusers.utils.testing_utils import enable_full_determinism, nightly, require_torch_gpu, skip_mps, 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 PipelineKarrasSchedulerTesterMixin, PipelineLatentTesterMixin, PipelineTesterMixin
label_desc: Use image node_id 4 for calling the StableDiffusionModelEditingSlowTests obj's underlying member method code with example usage: obj.test_stable_diffusion_model_editing_pipeline_with_sequential_cpu_offloading() without return types