code: def test_oracle_bad_tokenization(vocab, arc_eager):
      words_deps_heads = """
          [catalase] dep is
          : punct is
          that nsubj is
          is root is
          bad comp is
      """
  
      gold_words = []
      gold_deps = []
      gold_heads = []
      for line in words_deps_heads.strip().split("\n"):
          line = line.strip()
          if not line:
              continue
          word, dep, head = line.split()
          gold_words.append(word)
          gold_deps.append(dep)
          gold_heads.append(head)
      gold_heads = [gold_words.index(head) for head in gold_heads]
      for dep in gold_deps:
          arc_eager.add_action(2, dep)  # Left
          arc_eager.add_action(3, dep)  # Right
      reference = Doc(
          Vocab(), words=gold_words, deps=gold_deps, heads=gold_heads
      )
      predicted = Doc(
          reference.vocab,
          words=["[", "catalase", "]", ":", "that", "is", "bad"],
      )
      example = Example(predicted=predicted, reference=reference)
      ae_oracle_actions = arc_eager.get_oracle_sequence(
          example, _debug=False
      )
      ae_oracle_actions = [
          arc_eager.get_class_name(i) for i in ae_oracle_actions
      ]
      assert ae_oracle_actions
  
file_path: spaCy/spacy/tests/parser/test_arc_eager_oracle.py
imports: import pytest
  from spacy import registry
  from spacy.pipeline import DependencyParser
  from spacy.pipeline._parser_internals.arc_eager import ArcEager
  from spacy.pipeline._parser_internals.nonproj import projectivize
  from spacy.pipeline.dep_parser import DEFAULT_PARSER_MODEL
  from spacy.tokens import Doc
  from spacy.training import Example
  from spacy.vocab import Vocab
label_desc: Use image node_id 8 for calling a global function with example usage: test_oracle_bad_tokenization(vocab, arc_eager) without return types