code: def test_issue3540(en_vocab):
      words = ["I", "live", "in", "NewYork", "right", "now"]
      tensor = numpy.asarray(
          [
              [1.0, 1.1],
              [2.0, 2.1],
              [3.0, 3.1],
              [4.0, 4.1],
              [5.0, 5.1],
              [6.0, 6.1],
          ],
          dtype="f",
      )
      doc = Doc(en_vocab, words=words)
      doc.tensor = tensor
      gold_text = ["I", "live", "in", "NewYork", "right", "now"]
      assert [token.text for token in doc] == gold_text
      gold_lemma = ["I", "live", "in", "NewYork", "right", "now"]
      for i, lemma in enumerate(gold_lemma):
          doc[i].lemma_ = lemma
      assert [token.lemma_ for token in doc] == gold_lemma
      vectors_1 = [token.vector for token in doc]
      assert len(vectors_1) == len(doc)
  
      with doc.retokenize() as retokenizer:
          heads = [(doc[3], 1), doc[2]]
          attrs = {
              "POS": ["PROPN", "PROPN"],
              "LEMMA": ["New", "York"],
              "DEP": ["pobj", "compound"],
          }
          retokenizer.split(
              doc[3], ["New", "York"], heads=heads, attrs=attrs
          )
  
      gold_text = ["I", "live", "in", "New", "York", "right", "now"]
      assert [token.text for token in doc] == gold_text
      gold_lemma = ["I", "live", "in", "New", "York", "right", "now"]
      assert [token.lemma_ for token in doc] == gold_lemma
      vectors_2 = [token.vector for token in doc]
      assert len(vectors_2) == len(doc)
      assert vectors_1[0].tolist() == vectors_2[0].tolist()
      assert vectors_1[1].tolist() == vectors_2[1].tolist()
      assert vectors_1[2].tolist() == vectors_2[2].tolist()
      assert vectors_1[4].tolist() == vectors_2[5].tolist()
      assert vectors_1[5].tolist() == vectors_2[6].tolist()
  
file_path: spacy/spacy/tests/doc/test_retokenize_split.py
imports: import numpy
  import pytest
  from spacy.tokens import Doc, Token
  from spacy.vocab import Vocab
label_desc: Use image node_id 1 for calling a global function with example usage: test_issue3540(en_vocab) without return types