code: def get_dummy_inputs_2images(self, device, seed=0, img_res=64):
      # Get random floats in [0, 1] as image with spatial size (img_res, img_res)
      image1 = floats_tensor(
          (1, 3, img_res, img_res), rng=random.Random(seed)
      ).to(device)
      image2 = floats_tensor(
          (1, 3, img_res, img_res), rng=random.Random(seed + 22)
      ).to(device)
      # Convert images to [-1, 1]
      init_image1 = 2.0 * image1 - 1.0
      init_image2 = 2.0 * image2 - 1.0
  
      # empty mask
      mask_image = torch.zeros((1, 1, img_res, img_res), device=device)
  
      if str(device).startswith("mps"):
          generator1 = torch.manual_seed(seed)
          generator2 = torch.manual_seed(seed)
      else:
          generator1 = torch.Generator(device=device).manual_seed(seed)
          generator2 = torch.Generator(device=device).manual_seed(seed)
  
      inputs = {
          "prompt": ["A painting of a squirrel eating a burger"] * 2,
          "image": [init_image1, init_image2],
          "mask_image": [mask_image] * 2,
          "generator": [generator1, generator2],
          "num_inference_steps": 2,
          "guidance_scale": 6.0,
          "output_type": "np",
      }
      return inputs
  
imports: import copy
  import random
  import unittest
  import numpy
  import torch
  from PIL import Image
  from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
  from diffusers import AutoencoderKL, DDIMScheduler, DPMSolverMultistepScheduler, EulerDiscreteScheduler, HeunDiscreteScheduler, StableDiffusionXLInpaintPipeline, UNet2DConditionModel, UniPCMultistepScheduler
  from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, require_torch_gpu, torch_device
  from ..pipeline_params import TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS, TEXT_GUIDED_IMAGE_INPAINTING_PARAMS
  from ..test_pipelines_common import PipelineLatentTesterMixin, PipelineTesterMixin
label_desc: Use image node_id 3 for calling the StableDiffusionXLInpaintPipelineFastTests obj's underlying member method code with example usage: obj.get_dummy_inputs_2images(device, seed, img_res) and returns: inputs