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9d3ce7cba2
* unit test for previously resolved unflatten issue * prevent batch of empty docs to cause problems
24 lines
687 B
Python
24 lines
687 B
Python
# coding: utf8
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from __future__ import unicode_literals
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from spacy.lang.en import English
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from spacy.util import minibatch, compounding
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def test_issue4348():
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"""Test that training the tagger with empty data, doesn't throw errors"""
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TRAIN_DATA = [("", {"tags": []}), ("", {"tags": []})]
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nlp = English()
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tagger = nlp.create_pipe("tagger")
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nlp.add_pipe(tagger)
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optimizer = nlp.begin_training()
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for i in range(5):
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losses = {}
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batches = minibatch(TRAIN_DATA, size=compounding(4.0, 32.0, 1.001))
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for batch in batches:
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texts, annotations = zip(*batch)
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nlp.update(texts, annotations, sgd=optimizer, losses=losses)
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