code: def prepare_optical_flow_images():
      dataset = load_dataset(
          "hf-internal-testing/fixtures_sintel", split="test"
      )
      image1 = Image.open(dataset[0]["file"]).convert("RGB")
      image2 = Image.open(dataset[0]["file"]).convert("RGB")
  
      return image1, image2
  
imports: import copy
  import inspect
  import math
  import tempfile
  import unittest
  import warnings
  from typing import Dict, List, Tuple
  import numpy
  from datasets import load_dataset
  from transformers import PerceiverConfig
  from transformers.models.auto import get_values
  from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
  from transformers.utils import is_torch_available, is_vision_available
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
label_desc: Use image node_id 2 for calling a global function with example usage: prepare_optical_flow_images() and returns: image1,  image2