code: def get_test_pipeline(self, model, tokenizer, feature_extractor):
      if isinstance(model.config, LxmertConfig):
          # This is an bimodal model, we need to find a more consistent way
          # to switch on those models.
          return None, None
      question_answerer = QuestionAnsweringPipeline(model, tokenizer)
  
      examples = [
          {
              "question": "Where was HuggingFace founded ?",
              "context": "HuggingFace was founded in Paris.",
          },
          {
              "question": "In what field is HuggingFace ?",
              "context": "HuggingFace is  an AI startup.",
          },
      ]
      return question_answerer, examples
  
imports: import unittest
  from transformers import MODEL_FOR_QUESTION_ANSWERING_MAPPING, TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING, LxmertConfig, QuestionAnsweringPipeline
  from transformers.data.processors.squad import SquadExample
  from transformers.pipelines import QuestionAnsweringArgumentHandler, pipeline
  from transformers.testing_utils import nested_simplify, require_tf, require_torch, require_torch_or_tf, slow
  from .test_pipelines_common import ANY, PipelineTestCaseMeta
label_desc: Use image node_id 1 for calling the QAPipelineTests obj's underlying member method code with example usage: obj.get_test_pipeline(model, tokenizer, feature_extractor) and returns: question_answerer,  examples, None,  None