code: def test_split_into_words():
      text = "hi yo"
      char_to_word_offset = [0, 0, 0, 1, 1]
      doc_tokens = ["hi", "yo"]
      output = SquadDataset.split_into_words(text)
      assert output[0] == doc_tokens
      assert output[1] == char_to_word_offset
  
      text = "i am good"
      char_to_word_offset = [0, 0, 1, 1, 1, 2, 2, 2, 2]
      doc_tokens = ["i", "am", "good"]
      output = SquadDataset.split_into_words(text)
      assert output[0] == doc_tokens
      assert output[1] == char_to_word_offset
  
file_path: NeMo/tests/collections/nlp/test_question_answering.py
imports: import collections
  from pydoc import doc
  import pytest
  from nemo.collections.nlp.data.question_answering_squad.qa_dataset import SquadDataset
  from nemo.collections.nlp.data.question_answering_squad.qa_squad_processing import _get_tokens, exact_match_score, f1_score
label_desc: Use image node_id 4 for calling a global function with example usage: test_split_into_words() without return types