spaCy/spacy/tests/regression/test_issue4725.py

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# coding: utf8
from __future__ import unicode_literals
import numpy
from spacy.lang.en import English
from spacy.vocab import Vocab
def test_issue4725():
# ensures that this runs correctly and doesn't hang or crash because of the global vectors
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)
ner = nlp.create_pipe("ner")
nlp.add_pipe(ner)
nlp.begin_training()
docs = ["Kurt is in London."] * 10
for _ in nlp.pipe(docs, batch_size=2, n_process=2):
pass