code: def test_remove_unused_weights_save_load(self):
      pipe = VersatileDiffusionTextToImagePipeline.from_pretrained(
          "shi-labs/versatile-diffusion"
      )
      # remove text_unet
      pipe.remove_unused_weights()
      pipe.to(torch_device)
      pipe.set_progress_bar_config(disable=None)
  
      prompt = "A painting of a squirrel eating a burger "
      generator = torch.manual_seed(0)
      image = pipe(
          prompt=prompt,
          generator=generator,
          guidance_scale=7.5,
          num_inference_steps=2,
          output_type="numpy",
      ).images
  
      with tempfile.TemporaryDirectory() as tmpdirname:
          pipe.save_pretrained(tmpdirname)
          pipe = VersatileDiffusionTextToImagePipeline.from_pretrained(
              tmpdirname
          )
      pipe.to(torch_device)
      pipe.set_progress_bar_config(disable=None)
  
      generator = generator.manual_seed(0)
      new_image = pipe(
          prompt=prompt,
          generator=generator,
          guidance_scale=7.5,
          num_inference_steps=2,
          output_type="numpy",
      ).images
  
      assert (
          np.abs(image - new_image).max() < 1e-5
      ), "Models don't have the same forward pass"
  
file_path: llmga/llmga/diffusers/tests/pipelines/versatile_diffusion/test_versatile_diffusion_text_to_image.py
imports: import gc
  import tempfile
  import unittest
  import numpy
  import torch
  from diffusers import VersatileDiffusionTextToImagePipeline
  from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
label_desc: Use image node_id 2 for calling the VersatileDiffusionTextToImagePipelineIntegrationTests obj's underlying member method code with example usage: obj.test_remove_unused_weights_save_load() without return types