code: def test_roberta():
      reader = ExtractiveReader("deepset/tinyroberta-squad2")
      reader.warm_up()
      answers = reader.run(
          example_queries[0], example_documents[0], top_k=2
      )[
          "answers"
      ]  # remove indices when batching is reintroduced
      assert answers[0].data == "Olaf Scholz"
      assert answers[0].score == pytest.approx(0.8614975214004517)
      assert answers[1].data == "Angela Merkel"
      assert answers[1].score == pytest.approx(0.857952892780304)
      assert answers[2].data is None
      assert answers[2].score == pytest.approx(0.019673851661650588)
      assert len(answers) == 3
  
imports: from math import ceil, exp
  from typing import List
  from unittest.mock import patch, Mock
  import pytest
  import torch
  from transformers import pipeline
  from haystack.components.readers import ExtractiveReader
  from haystack import Document, ExtractedAnswer
label_desc: Use image node_id 14 for calling a global function with example usage: test_roberta() without return types