code: def test_sentencizer_empty_docs():
      one_empty_text = [""]
      many_empty_texts = ["", "", ""]
      some_empty_texts = [
          "hi",
          "",
          "This is a test. Here are two sentences.",
          "",
      ]
      nlp = English()
      nlp.add_pipe("sentencizer")
      for texts in [one_empty_text, many_empty_texts, some_empty_texts]:
          for doc in nlp.pipe(texts):
              assert doc.has_annotation("SENT_START")
              sent_starts = [t.is_sent_start for t in doc]
              if len(doc) == 0:
                  assert sent_starts == []
              else:
                  assert len(sent_starts) > 0
  
file_path: spacy/spacy/tests/pipeline/test_sentencizer.py
imports: import pytest
  import spacy
  from spacy.lang.en import English
  from spacy.pipeline import Sentencizer
  from spacy.tokens import Doc
label_desc: Use image node_id 3 for calling a global function with example usage: test_sentencizer_empty_docs() without return types