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505c6a2f2f
Tokenizer cache can have be different keys than string That modification can slow down tokenizer and need to be measured
36 lines
918 B
Python
36 lines
918 B
Python
# coding: utf8
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from __future__ import unicode_literals
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import gc
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from ...lang.en import English
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def test_issue1506():
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nlp = English()
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def string_generator():
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for _ in range(10001):
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yield u"It's sentence produced by that bug."
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for _ in range(10001):
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yield u"I erase some hbdsaj lemmas."
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for _ in range(10001):
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yield u"I erase lemmas."
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for _ in range(10001):
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yield u"It's sentence produced by that bug."
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for _ in range(10001):
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yield u"It's sentence produced by that bug."
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for i, d in enumerate(nlp.pipe(string_generator())):
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# We should run cleanup more than one time to actually cleanup data.
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# In first run — clean up only mark strings as «not hitted».
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if i == 10000 or i == 20000 or i == 30000:
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gc.collect()
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for t in d:
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str(t.lemma_)
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