code: def get_test_pipeline(self, model, tokenizer, feature_extractor):
      vqa_pipeline = pipeline(
          "visual-question-answering",
          model="hf-internal-testing/tiny-vilt-random-vqa",
      )
      examples = [
          {
              "image": Image.open(
                  "./tests/fixtures/tests_samples/COCO/000000039769.png"
              ),
              "question": "How many cats are there?",
          },
          {
              "image": "./tests/fixtures/tests_samples/COCO/000000039769.png",
              "question": "How many cats are there?",
          },
      ]
      return vqa_pipeline, examples
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/tests/pipelines/test_pipelines_visual_question_answering.py
imports: import unittest
  from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
  from transformers.pipelines import pipeline
  from transformers.testing_utils import nested_simplify, require_tf, require_torch, require_vision, slow
  from .test_pipelines_common import ANY, PipelineTestCaseMeta
label_desc: Use image node_id 1 for calling the VisualQuestionAnsweringPipelineTests obj's underlying member method code with example usage: obj.get_test_pipeline(model, tokenizer, feature_extractor) and returns: vqa_pipeline,  examples