code: def test_text_to_image_sdxl(self):
      image_encoder = self.get_image_encoder(
          repo_id="h94/IP-Adapter",
          subfolder="sdxl_models/image_encoder",
      )
      feature_extractor = self.get_image_processor(
          "laion/CLIP-ViT-bigG-14-laion2B-39B-b160k"
      )
  
      pipeline = StableDiffusionXLPipeline.from_pretrained(
          "stabilityai/stable-diffusion-xl-base-1.0",
          image_encoder=image_encoder,
          feature_extractor=feature_extractor,
          torch_dtype=self.dtype,
      )
      pipeline.to(torch_device)
      pipeline.load_ip_adapter(
          "h94/IP-Adapter",
          subfolder="sdxl_models",
          weight_name="ip-adapter_sdxl.bin",
      )
  
      inputs = self.get_dummy_inputs()
      images = pipeline(**inputs).images
      image_slice = images[0, :3, :3, -1].flatten()
  
      expected_slice = np.array(
          [
              0.0965,
              0.0956,
              0.0849,
              0.0908,
              0.0944,
              0.0927,
              0.0888,
              0.0929,
              0.0920,
          ]
      )
  
      assert np.allclose(
          image_slice, expected_slice, atol=1e-4, rtol=1e-4
      )
  
      image_encoder = self.get_image_encoder(
          repo_id="h94/IP-Adapter", subfolder="models/image_encoder"
      )
  
      pipeline = StableDiffusionXLPipeline.from_pretrained(
          "stabilityai/stable-diffusion-xl-base-1.0",
          image_encoder=image_encoder,
          feature_extractor=feature_extractor,
          torch_dtype=self.dtype,
      )
      pipeline.to(torch_device)
      pipeline.load_ip_adapter(
          "h94/IP-Adapter",
          subfolder="sdxl_models",
          weight_name="ip-adapter-plus_sdxl_vit-h.bin",
      )
  
      inputs = self.get_dummy_inputs()
      images = pipeline(**inputs).images
      image_slice = images[0, :3, :3, -1].flatten()
  
      expected_slice = np.array(
          [
              0.0592,
              0.0573,
              0.0459,
              0.0542,
              0.0559,
              0.0523,
              0.0500,
              0.0540,
              0.0501,
          ]
      )
  
      assert np.allclose(
          image_slice, expected_slice, atol=1e-4, rtol=1e-4
      )
  
imports: import gc
  import unittest
  import numpy
  import torch
  from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
  from diffusers import StableDiffusionImg2ImgPipeline, StableDiffusionInpaintPipeline, StableDiffusionPipeline, StableDiffusionXLImg2ImgPipeline, StableDiffusionXLInpaintPipeline, StableDiffusionXLPipeline
  from diffusers.models.attention_processor import AttnProcessor, AttnProcessor2_0
  from diffusers.utils import load_image
  from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
label_desc: Use image node_id 1 for calling the IPAdapterSDXLIntegrationTests obj's underlying member method code with example usage: obj.test_text_to_image_sdxl() without return types