code: def test_issue4725_2():
      if isinstance(get_current_ops, NumpyOps):
          # ensures that this runs correctly and doesn't hang or crash because of the global vectors
          # if it does crash, it's usually because of calling 'spawn' for multiprocessing (e.g. on Windows),
          # or because of issues with pickling the NER (cf test_issue4725_1)
          vocab = Vocab(vectors_name="test_vocab_add_vector")
          data = numpy.ndarray((5, 3), dtype="f")
          data[0] = 1.0
          data[1] = 2.0
          vocab.set_vector("cat", data[0])
          vocab.set_vector("dog", data[1])
          nlp = English(vocab=vocab)
          nlp.add_pipe("ner")
          nlp.initialize()
          docs = ["Kurt is in London."] * 10
          for _ in nlp.pipe(docs, batch_size=2, n_process=2):
              pass
  
imports: import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_almost_equal, assert_equal
  from thinc.api import NumpyOps, get_current_ops
  from spacy.lang.en import English
  from spacy.strings import hash_string
  from spacy.tokenizer import Tokenizer
  from spacy.tokens import Doc
  from spacy.training.initialize import convert_vectors
  from spacy.vectors import Vectors
  from spacy.vocab import Vocab
  from ..util import add_vecs_to_vocab, get_cosine, make_tempdir
label_desc: Use image node_id 14 for calling a global function with example usage: test_issue4725_2() without return types