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26 lines
683 B
Python
26 lines
683 B
Python
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# coding: utf8
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from __future__ import unicode_literals
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import numpy
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from spacy.lang.en import English
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from spacy.vocab import Vocab
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def test_issue4725():
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# ensures that this runs correctly and doesn't hang or crash because of the global vectors
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vocab = Vocab(vectors_name="test_vocab_add_vector")
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data = numpy.ndarray((5, 3), dtype="f")
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data[0] = 1.0
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data[1] = 2.0
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vocab.set_vector("cat", data[0])
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vocab.set_vector("dog", data[1])
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nlp = English(vocab=vocab)
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ner = nlp.create_pipe("ner")
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nlp.add_pipe(ner)
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nlp.begin_training()
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docs = ["Kurt is in London."] * 10
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for _ in nlp.pipe(docs, batch_size=2, n_process=2):
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pass
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