code: def run_pipeline_test(self, question_answerer, _):
      outputs = question_answerer(
          question="Where was HuggingFace founded ?",
          context="HuggingFace was founded in Paris.",
      )
      self.assertEqual(
          outputs,
          {
              "answer": ANY(str),
              "start": ANY(int),
              "end": ANY(int),
              "score": ANY(float),
          },
      )
      outputs = question_answerer(
          question="Where was HuggingFace founded ?",
          context="HuggingFace was founded in Paris.",
          handle_impossible_answer=True,
      )
      self.assertEqual(
          outputs,
          {
              "answer": ANY(str),
              "start": ANY(int),
              "end": ANY(int),
              "score": ANY(float),
          },
      )
  
      outputs = question_answerer(
          question=[
              "In what field is HuggingFace working ?",
              "In what field is HuggingFace working ?",
          ],
          context="HuggingFace was founded in Paris.",
      )
      self.assertEqual(
          outputs,
          [
              {
                  "answer": ANY(str),
                  "start": ANY(int),
                  "end": ANY(int),
                  "score": ANY(float),
              },
              {
                  "answer": ANY(str),
                  "start": ANY(int),
                  "end": ANY(int),
                  "score": ANY(float),
              },
          ],
      )
  
      outputs = question_answerer(
          question=[
              "What field is HuggingFace working ?",
              "In what field is HuggingFace ?",
          ],
          context=[
              "HuggingFace is a startup based in New-York",
              "HuggingFace is a startup founded in Paris",
          ],
      )
      self.assertEqual(
          outputs,
          [
              {
                  "answer": ANY(str),
                  "start": ANY(int),
                  "end": ANY(int),
                  "score": ANY(float),
              },
              {
                  "answer": ANY(str),
                  "start": ANY(int),
                  "end": ANY(int),
                  "score": ANY(float),
              },
          ],
      )
  
      with self.assertRaises(ValueError):
          question_answerer(
              question="", context="HuggingFace was founded in Paris."
          )
      with self.assertRaises(ValueError):
          question_answerer(
              question=None, context="HuggingFace was founded in Paris."
          )
      with self.assertRaises(ValueError):
          question_answerer(
              question="In what field is HuggingFace working ?",
              context="",
          )
      with self.assertRaises(ValueError):
          question_answerer(
              question="In what field is HuggingFace working ?",
              context=None,
          )
  
      outputs = question_answerer(
          question="Where was HuggingFace founded ?",
          context="HuggingFace was founded in Paris.",
          top_k=20,
      )
      self.assertEqual(
          outputs,
          [
              {
                  "answer": ANY(str),
                  "start": ANY(int),
                  "end": ANY(int),
                  "score": ANY(float),
              }
              for i in range(20)
          ],
      )
  
      # Very long context require multiple features
      outputs = question_answerer(
          question="Where was HuggingFace founded ?",
          context="HuggingFace was founded in Paris." * 20,
      )
      self.assertEqual(
          outputs,
          {
              "answer": ANY(str),
              "start": ANY(int),
              "end": ANY(int),
              "score": ANY(float),
          },
      )
  
      # Using batch is OK
      if question_answerer.tokenizer.pad_token_id is None:
          question_answerer.tokenizer.pad_token_id = (
              question_answerer.model.config.eos_token_id
          )
      new_outputs = question_answerer(
          question="Where was HuggingFace founded ?",
          context="HuggingFace was founded in Paris." * 20,
          batch_size=2,
      )
      self.assertEqual(
          new_outputs,
          {
              "answer": ANY(str),
              "start": ANY(int),
              "end": ANY(int),
              "score": ANY(float),
          },
      )
      self.assertEqual(
          nested_simplify(outputs), nested_simplify(new_outputs)
      )
  
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 is_pipeline_test, nested_simplify, require_tf, require_torch, require_torch_or_tf, slow
  from .test_pipelines_common import ANY
label_desc: Use image node_id 2 for calling the QAPipelineTests obj's underlying member method code with example usage: obj.run_pipeline_test(question_answerer, _) without return types