mirror of
https://github.com/explosion/spaCy.git
synced 2024-12-27 18:36:36 +03:00
Merge branch 'develop' into spacy.io
This commit is contained in:
Ines Montani
commit
ab8392eda3
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@ -10,12 +10,13 @@ Compatible with: spaCy v2.0.0+
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"""
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from __future__ import print_function, unicode_literals
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from toolz import partition_all
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from pathlib import Path
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from joblib import Parallel, delayed
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from functools import partial
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import thinc.extra.datasets
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import plac
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import spacy
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from spacy.util import minibatch
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@plac.annotations(
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@ -35,10 +36,10 @@ def main(output_dir, model="en_core_web_sm", n_jobs=4, batch_size=1000, limit=10
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data, _ = thinc.extra.datasets.imdb()
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texts, _ = zip(*data[-limit:])
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print("Processing texts...")
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partitions = partition_all(batch_size, texts)
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executor = Parallel(n_jobs=n_jobs)
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do = delayed(transform_texts)
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tasks = (do(nlp, i, batch, output_dir) for i, batch in enumerate(partitions))
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partitions = minibatch(texts, size=batch_size)
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executor = Parallel(n_jobs=n_jobs, backend="multiprocessing", prefer="processes")
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do = delayed(partial(transform_texts, nlp))
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tasks = (do(i, batch, output_dir) for i, batch in enumerate(partitions))
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executor(tasks)
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@ -31,7 +31,7 @@ TAG_MAP = {"N": {"pos": "NOUN"}, "V": {"pos": "VERB"}, "J": {"pos": "ADJ"}}
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# strings are unicode and that the number of tags assigned matches spaCy's
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# tokenization. If not, you can always add a 'words' key to the annotations
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# that specifies the gold-standard tokenization, e.g.:
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# ("Eatblueham", {'words': ['Eat', 'blue', 'ham'] 'tags': ['V', 'J', 'N']})
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# ("Eatblueham", {'words': ['Eat', 'blue', 'ham'], 'tags': ['V', 'J', 'N']})
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TRAIN_DATA = [
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("I like green eggs", {"tags": ["N", "V", "J", "N"]}),
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("Eat blue ham", {"tags": ["V", "J", "N"]}),
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1
fabfile.py
vendored
1
fabfile.py
vendored
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@ -59,6 +59,7 @@ def make():
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def sdist():
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with virtualenv(VENV_DIR) as venv_local:
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with lcd(path.dirname(__file__)):
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local('python -m pip install -U setuptools')
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local('python setup.py sdist')
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def wheel():
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@ -4,7 +4,7 @@
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# fmt: off
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__title__ = "spacy-nightly"
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__version__ = "2.1.0a7"
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__version__ = "2.1.0a8"
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__summary__ = "Industrial-strength Natural Language Processing (NLP) with Python and Cython"
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__uri__ = "https://spacy.io"
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__author__ = "Explosion AI"
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@ -5,41 +5,143 @@ split_chars = lambda char: list(char.strip().split(" "))
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merge_chars = lambda char: char.strip().replace(" ", "|")
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group_chars = lambda char: char.strip().replace(" ", "")
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# used https://unicode.org/cldr/utility/list-unicodeset.jsp to convert categories into code points
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# \p{L}&&\p{Bengali}
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# https://en.wikipedia.org/wiki/Bengali_(Unicode_block)
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_bengali = r"\u0980-\u09FF"
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# \p{L}&&\p{Hebrew}
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# https://en.wikipedia.org/wiki/Unicode_and_HTML_for_the_Hebrew_alphabet
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_hebrew = r"\u0591-\u05F4\uFB1D-\uFB4F"
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# \p{Ll}&&\p{Latin}
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_latin_lower = r"a-z\u00DF-\u00F6\u00F8-\u00FF\u0101\u0103\u0105\u0107\u0109\u010B\u010D\u010F\u0111\u0113\u0115\u0117\u0119\u011B\u011D\u011F\u0121\u0123\u0125\u0127\u0129\u012B\u012D\u012F\u0131\u0133\u0135\u0137\u0138\u013A\u013C\u013E\u0140\u0142\u0144\u0146\u0148\u0149\u014B\u014D\u014F\u0151\u0153\u0155\u0157\u0159\u015B\u015D\u015F\u0161\u0163\u0165\u0167\u0169\u016B\u016D\u016F\u0171\u0173\u0175\u0177\u017A\u017C\u017E-\u0180\u0183\u0185\u0188\u018C\u018D\u0192\u0195\u0199-\u019B\u019E\u01A1\u01A3\u01A5\u01A8\u01AA\u01AB\u01AD\u01B0\u01B4\u01B6\u01B9\u01BA\u01BD-\u01BF\u01C6\u01C9\u01CC\u01CE\u01D0\u01D2\u01D4\u01D6\u01D8\u01DA\u01DC\u01DD\u01DF\u01E1\u01E3\u01E5\u01E7\u01E9\u01EB\u01ED\u01EF\u01F0\u01F3\u01F5\u01F9\u01FB\u01FD\u01FF\u0201\u0203\u0205\u0207\u0209\u020B\u020D\u020F\u0211\u0213\u0215\u0217\u0219\u021B\u021D\u021F\u0221\u0223\u0225\u0227\u0229\u022B\u022D\u022F\u0231\u0233-\u0239\u023C\u023F\u0240\u0242\u0247\u0249\u024B\u024D\u024F-\u0293\u0295-\u02AF\u1D00-\u1D25\u1D6B-\u1D77\u1D79-\u1D9A\u1E01\u1E03\u1E05\u1E07\u1E09\u1E0B\u1E0D\u1E0F\u1E11\u1E13\u1E15\u1E17\u1E19\u1E1B\u1E1D\u1E1F\u1E21\u1E23\u1E25\u1E27\u1E29\u1E2B\u1E2D\u1E2F\u1E31\u1E33\u1E35\u1E37\u1E39\u1E3B\u1E3D\u1E3F\u1E41\u1E43\u1E45\u1E47\u1E49\u1E4B\u1E4D\u1E4F\u1E51\u1E53\u1E55\u1E57\u1E59\u1E5B\u1E5D\u1E5F\u1E61\u1E63\u1E65\u1E67\u1E69\u1E6B\u1E6D\u1E6F\u1E71\u1E73\u1E75\u1E77\u1E79\u1E7B\u1E7D\u1E7F\u1E81\u1E83\u1E85\u1E87\u1E89\u1E8B\u1E8D\u1E8F\u1E91\u1E93\u1E95-\u1E9D\u1E9F\u1EA1\u1EA3\u1EA5\u1EA7\u1EA9\u1EAB\u1EAD\u1EAF\u1EB1\u1EB3\u1EB5\u1EB7\u1EB9\u1EBB\u1EBD\u1EBF\u1EC1\u1EC3\u1EC5\u1EC7\u1EC9\u1ECB\u1ECD\u1ECF\u1ED1\u1ED3\u1ED5\u1ED7\u1ED9\u1EDB\u1EDD\u1EDF\u1EE1\u1EE3\u1EE5\u1EE7\u1EE9\u1EEB\u1EED\u1EEF\u1EF1\u1EF3\u1EF5\u1EF7\u1EF9\u1EFB\u1EFD\u1EFF\u214E\u2184\u2C61\u2C65\u2C66\u2C68\u2C6A\u2C6C\u2C71\u2C73\u2C74\u2C76-\u2C7B\uA723\uA725\uA727\uA729\uA72B\uA72D\uA72F-\uA731\uA733\uA735\uA737\uA739\uA73B\uA73D\uA73F\uA741\uA743\uA745\uA747\uA749\uA74B\uA74D\uA74F\uA751\uA753\uA755\uA757\uA759\uA75B\uA75D\uA75F\uA761\uA763\uA765\uA767\uA769\uA76B\uA76D\uA76F\uA771-\uA778\uA77A\uA77C\uA77F\uA781\uA783\uA785\uA787\uA78C\uA78E\uA791\uA793-\uA795\uA797\uA799\uA79B\uA79D\uA79F\uA7A1\uA7A3\uA7A5\uA7A7\uA7A9\uA7AF\uA7B5\uA7B7\uA7B9\uA7FA\uAB30-\uAB5A\uAB60-\uAB64\uFB00-\uFB06\uFF41-\uFF5A"
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# \p{Lu}&&\p{Latin}
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_latin_upper = r"A-Z\u00C0-\u00D6\u00D8-\u00DE\u0100\u0102\u0104\u0106\u0108\u010A\u010C\u010E\u0110\u0112\u0114\u0116\u0118\u011A\u011C\u011E\u0120\u0122\u0124\u0126\u0128\u012A\u012C\u012E\u0130\u0132\u0134\u0136\u0139\u013B\u013D\u013F\u0141\u0143\u0145\u0147\u014A\u014C\u014E\u0150\u0152\u0154\u0156\u0158\u015A\u015C\u015E\u0160\u0162\u0164\u0166\u0168\u016A\u016C\u016E\u0170\u0172\u0174\u0176\u0178\u0179\u017B\u017D\u0181\u0182\u0184\u0186\u0187\u0189-\u018B\u018E-\u0191\u0193\u0194\u0196-\u0198\u019C\u019D\u019F\u01A0\u01A2\u01A4\u01A6\u01A7\u01A9\u01AC\u01AE\u01AF\u01B1-\u01B3\u01B5\u01B7\u01B8\u01BC\u01C4\u01C7\u01CA\u01CD\u01CF\u01D1\u01D3\u01D5\u01D7\u01D9\u01DB\u01DE\u01E0\u01E2\u01E4\u01E6\u01E8\u01EA\u01EC\u01EE\u01F1\u01F4\u01F6-\u01F8\u01FA\u01FC\u01FE\u0200\u0202\u0204\u0206\u0208\u020A\u020C\u020E\u0210\u0212\u0214\u0216\u0218\u021A\u021C\u021E\u0220\u0222\u0224\u0226\u0228\u022A\u022C\u022E\u0230\u0232\u023A\u023B\u023D\u023E\u0241\u0243-\u0246\u0248\u024A\u024C\u024E\u1E00\u1E02\u1E04\u1E06\u1E08\u1E0A\u1E0C\u1E0E\u1E10\u1E12\u1E14\u1E16\u1E18\u1E1A\u1E1C\u1E1E\u1E20\u1E22\u1E24\u1E26\u1E28\u1E2A\u1E2C\u1E2E\u1E30\u1E32\u1E34\u1E36\u1E38\u1E3A\u1E3C\u1E3E\u1E40\u1E42\u1E44\u1E46\u1E48\u1E4A\u1E4C\u1E4E\u1E50\u1E52\u1E54\u1E56\u1E58\u1E5A\u1E5C\u1E5E\u1E60\u1E62\u1E64\u1E66\u1E68\u1E6A\u1E6C\u1E6E\u1E70\u1E72\u1E74\u1E76\u1E78\u1E7A\u1E7C\u1E7E\u1E80\u1E82\u1E84\u1E86\u1E88\u1E8A\u1E8C\u1E8E\u1E90\u1E92\u1E94\u1E9E\u1EA0\u1EA2\u1EA4\u1EA6\u1EA8\u1EAA\u1EAC\u1EAE\u1EB0\u1EB2\u1EB4\u1EB6\u1EB8\u1EBA\u1EBC\u1EBE\u1EC0\u1EC2\u1EC4\u1EC6\u1EC8\u1ECA\u1ECC\u1ECE\u1ED0\u1ED2\u1ED4\u1ED6\u1ED8\u1EDA\u1EDC\u1EDE\u1EE0\u1EE2\u1EE4\u1EE6\u1EE8\u1EEA\u1EEC\u1EEE\u1EF0\u1EF2\u1EF4\u1EF6\u1EF8\u1EFA\u1EFC\u1EFE\u212A\u212B\u2132\u2183\u2C60\u2C62-\u2C64\u2C67\u2C69\u2C6B\u2C6D-\u2C70\u2C72\u2C75\u2C7E\u2C7F\uA722\uA724\uA726\uA728\uA72A\uA72C\uA72E\uA732\uA734\uA736\uA738\uA73A\uA73C\uA73E\uA740\uA742\uA744\uA746\uA748\uA74A\uA74C\uA74E\uA750\uA752\uA754\uA756\uA758\uA75A\uA75C\uA75E\uA760\uA762\uA764\uA766\uA768\uA76A\uA76C\uA76E\uA779\uA77B\uA77D\uA77E\uA780\uA782\uA784\uA786\uA78B\uA78D\uA790\uA792\uA796\uA798\uA79A\uA79C\uA79E\uA7A0\uA7A2\uA7A4\uA7A6\uA7A8\uA7AA-\uA7AE\uA7B0-\uA7B4\uA7B6\uA7B8\uFF21-\uFF3A"
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# [\p{Ll}||\p{Lu}]&&\p{Latin}
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latin = r"A-Za-z\u00C0-\u00D6\u00D8-\u00F6\u00F8-\u01BA\u01BC-\u01BF\u01C4\u01C6\u01C7\u01C9\u01CA\u01CC-\u01F1\u01F3-\u0293\u0295-\u02AF\u1D00-\u1D25\u1D6B-\u1D77\u1D79-\u1D9A\u1E00-\u1EFF\u212A\u212B\u2132\u214E\u2183\u2184\u2C60-\u2C7B\u2C7E\u2C7F\uA722-\uA76F\uA771-\uA787\uA78B-\uA78E\uA790-\uA7B9\uA7FA\uAB30-\uAB5A\uAB60-\uAB64\uFB00-\uFB06\uFF21-\uFF3A\uFF41-\uFF5A"
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# Latin standard
|
||||
_latin_u_standard = r"A-Z"
|
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_latin_l_standard = r"a-z"
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_latin_standard = _latin_u_standard + _latin_l_standard
|
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|
||||
# \p{L}&&\p{Arabic}
|
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_persian = r"\u0620-\u064A\u066E-\u06D5\u06E5-\u06FF\u0750-\u077F\u08A0-\u08BD\uFB50-\uFBB1\uFBD3-\uFD3D\uFD50-\uFDC7\uFDF0-\uFDFB\uFE70-\uFEFC\U0001EE00-\U0001EEBB"
|
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_latin_u_standard_fullwidth = r"\uFF21-\uFF3A"
|
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_latin_l_standard_fullwidth = r"\uFF41-\uFF5A"
|
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_latin_standard_fullwidth = _latin_u_standard_fullwidth + _latin_l_standard_fullwidth
|
||||
|
||||
# letters with diacritics - French, German, Icelandic, Spanish
|
||||
_latin_u_supplement = r"\u00C0-\u00D6\u00D8-\u00DE"
|
||||
_latin_l_supplement = r"\u00DF-\u00F6\u00F8-\u00FF"
|
||||
_latin_supplement = r"\u00C0-\u00D6\u00D8-\u00F6\u00F8-\u00FF"
|
||||
|
||||
# letters with diacritics - Catalan, Czech, Latin, Latvian, Lithuanian, Polish, Slovak, Turkish, Welsh
|
||||
_latin_u_extendedA = r"\u0100\u0102\u0104\u0106\u0108\u010A\u010C\u010E\u0110\u0112\u0114\u0116\u0118\u011A\u011C" \
|
||||
r"\u011E\u0120\u0122\u0124\u0126\u0128\u012A\u012C\u012E\u0130\u0132\u0134\u0136\u0139\u013B" \
|
||||
r"\u013D\u013F\u0141\u0143\u0145\u0147\u014A\u014C\u014E\u0150\u0152\u0154\u0156\u0158" \
|
||||
r"\u015A\u015C\u015E\u0160\u0162\u0164\u0166\u0168\u016A\u016C\u016E\u0170\u0172\u0174\u0176" \
|
||||
r"\u0178\u0179\u017B\u017D"
|
||||
_latin_l_extendedA = r"\u0101\u0103\u0105\u0107\u0109\u010B\u010D\u010F\u0111\u0113\u0115\u0117\u0119\u011B\u011D" \
|
||||
r"\u011F\u0121\u0123\u0125\u0127\u0129\u012B\u012D\u012F\u0131\u0133\u0135\u0137\u0138\u013A" \
|
||||
r"\u013C\u013E\u0140\u0142\u0144\u0146\u0148\u0149\u014B\u014D\u014F\u0151\u0153\u0155\u0157" \
|
||||
r"\u0159\u015B\u015D\u015F\u0161\u0163\u0165\u0167\u0169\u016B\u016D\u016F\u0171\u0173\u0175" \
|
||||
r"\u0177\u017A\u017C\u017E\u017F"
|
||||
_latin_extendedA = r"\u0100-\u017F"
|
||||
|
||||
# special characters - Khoisan, Pan-Nigerian, Pinyin, Romanian
|
||||
# those that are a combination of both upper and lower letters are only included in the group _latin_extendedB
|
||||
_latin_u_extendedB = r"\u0181\u0182\u0184\u0186\u0187\u0189-\u018B\u018E-\u0191\u0193\u0194\u0196-\u0198\u019C" \
|
||||
r"\u019D\u019F\u01A0\u01A2\u01A4\u01A6\u01A7\u01A9\u01AC\u01AE\u01AF\u01B1-\u01B3\u01B5" \
|
||||
r"\u01B7\u01B8\u01BC\u01C4\u01C7\u01CA\u01CD\u01CF\u01D1\u01D3\u01D5\u01D7\u01D9\u01DB" \
|
||||
r"\u01DE\u01E0\u01E2\u01E4\u01E6\u01E8\u01EA\u01EC\u01EE\u01F1\u01F4\u01F6-\u01F8\u01FA" \
|
||||
r"\u01FC\u01FE\u0200\u0202\u0204\u0206\u0208\u020A\u020C\u020E\u0210\u0212\u0214\u0216" \
|
||||
r"\u0218\u021A\u021C\u021E\u0220\u0222\u0224\u0226\u0228\u022A\u022C\u022E\u0230\u0232" \
|
||||
r"\u023A\u023B\u023D\u023E\u0241\u0243-\u0246\u0248\u024A\u024C\u024E"
|
||||
_latin_l_extendedB = r"\u0180\u0183\u0185\u0188\u018C\u018D\u0192\u0195\u0199-\u019B\u019E\u01A1\u01A3\u01A5" \
|
||||
r"\u01A8\u01AA\u01AB\u01AD\u01B0\u01B4\u01B6\u01B9\u01BA\u01BD-\u01BF\u01C6\u01C9\u01CC" \
|
||||
r"\u01CE\u01D0\u01D2\u01D4\u01D6\u01D8\u01DA\u01DC\u01DD\u01DF\u01E1\u01E3\u01E5\u01E7" \
|
||||
r"\u01E9\u01EB\u01ED\u01EF\u01F0\u01F3\u01F5\u01F9\u01FB\u01FD\u01FF\u0201\u0203\u0205" \
|
||||
r"\u0207\u0209\u020B\u020D\u020F\u0211\u0213\u0215\u0217\u0219\u021B\u021D\u021F\u0221" \
|
||||
r"\u0223\u0225\u0227\u0229\u022B\u022D\u022F\u0231\u0233-\u0239\u023C\u023F\u0240\u0242" \
|
||||
r"\u0247\u0249\u024B\u024D\u024F"
|
||||
_latin_extendedB = r"\u0180-\u01BF\u01C4-\u024F"
|
||||
|
||||
# special characters - Uighur, Uralic Phonetic
|
||||
_latin_u_extendedC = r"\u2C60\u2C62-\u2C64\u2C67\u2C69\u2C6B\u2C6D-\u2C70\u2C72\u2C75\u2C7E\u2C7F"
|
||||
_latin_l_extendedC = r"\u2C61\u2C65\u2C66\u2C68\u2C6A\u2C6C\u2C71\u2C73\u2C74\u2C76-\u2C7B"
|
||||
_latin_extendedC = r"\u2C60-\u2C7B\u2C7E\u2C7F"
|
||||
|
||||
# special characters - phonetic, Mayan, Medieval
|
||||
_latin_u_extendedD = r"\uA722\uA724\uA726\uA728\uA72A\uA72C\uA72E\uA732\uA734\uA736\uA738\uA73A\uA73C" \
|
||||
r"\uA73E\uA740\uA742\uA744\uA746\uA748\uA74A\uA74C\uA74E\uA750\uA752\uA754\uA756\uA758" \
|
||||
r"\uA75A\uA75C\uA75E\uA760\uA762\uA764\uA766\uA768\uA76A\uA76C\uA76E\uA779\uA77B\uA77D" \
|
||||
r"\uA77E\uA780\uA782\uA784\uA786\uA78B\uA78D\uA790\uA792\uA796\uA798\uA79A\uA79C\uA79E" \
|
||||
r"\uA7A0\uA7A2\uA7A4\uA7A6\uA7A8\uA7AA-\uA7AE\uA7B0-\uA7B4\uA7B6\uA7B8"
|
||||
_latin_l_extendedD = r"\uA723\uA725\uA727\uA729\uA72B\uA72D\uA72F-\uA731\uA733\uA735\uA737\uA739\uA73B\uA73D" \
|
||||
r"\uA73F\uA741\uA743\uA745\uA747\uA749\uA74B\uA74D\uA74F\uA751\uA753\uA755\uA757\uA759" \
|
||||
r"\uA75B\uA75D\uA75F\uA761\uA763\uA765\uA767\uA769\uA76B\uA76D\uA76F\uA771-\uA778\uA77A" \
|
||||
r"\uA77C\uA77F\uA781\uA783\uA785\uA787\uA78C\uA78E\uA791\uA793-\uA795\uA797\uA799\uA79B" \
|
||||
r"\uA79D\uA79F\uA7A1\uA7A3\uA7A5\uA7A7\uA7A9\uA7AF\uA7B5\uA7B7\uA7B9\uA7FA"
|
||||
_latin_extendedD = r"\uA722-\uA76F\uA771-\uA787\uA78B-\uA78E\uA790-\uA7B9\uA7FA"
|
||||
|
||||
# special characters - phonetic Teuthonista and Sakha
|
||||
_latin_l_extendedE = r"\uAB30-\uAB5A\uAB60-\uAB64"
|
||||
_latin_extendedE = _latin_l_extendedE
|
||||
|
||||
# phonetic letters - Greek, Latin, Cyrillic
|
||||
_latin_l_phonetic = r"\u0250-\u02AF\u1D00-\u1D25\u1D6B-\u1D77\u1D79-\u1D9A"
|
||||
_latin_phonetic = _latin_l_phonetic
|
||||
|
||||
# letters with multiple diacritics - Vietnamese
|
||||
_latin_u_diacritics = r"\u1E00\u1E02\u1E04\u1E06\u1E08\u1E0A\u1E0C\u1E0E\u1E10\u1E12\u1E14\u1E16\u1E18\u1E1A" \
|
||||
r"\u1E1C\u1E1E\u1E20\u1E22\u1E24\u1E26\u1E28\u1E2A\u1E2C\u1E2E\u1E30\u1E32\u1E34\u1E36" \
|
||||
r"\u1E38\u1E3A\u1E3C\u1E3E\u1E40\u1E42\u1E44\u1E46\u1E48\u1E4A\u1E4C\u1E4E\u1E50\u1E52" \
|
||||
r"\u1E54\u1E56\u1E58\u1E5A\u1E5C\u1E5E\u1E60\u1E62\u1E64\u1E66\u1E68\u1E6A\u1E6C\u1E6E" \
|
||||
r"\u1E70\u1E72\u1E74\u1E76\u1E78\u1E7A\u1E7C\u1E7E\u1E80\u1E82\u1E84\u1E86\u1E88\u1E8A" \
|
||||
r"\u1E8C\u1E8E\u1E90\u1E92\u1E94\u1E9E\u1EA0\u1EA2\u1EA4\u1EA6\u1EA8\u1EAA\u1EAC\u1EAE" \
|
||||
r"\u1EB0\u1EB2\u1EB4\u1EB6\u1EB8\u1EBA\u1EBC\u1EBE\u1EC0\u1EC2\u1EC4\u1EC6\u1EC8" \
|
||||
r"\u1ECA\u1ECC\u1ECE\u1ED0\u1ED2\u1ED4\u1ED6\u1ED8\u1EDA\u1EDC\u1EDE\u1EE0\u1EE2\u1EE4" \
|
||||
r"\u1EE6\u1EE8\u1EEA\u1EEC\u1EEE\u1EF0\u1EF2\u1EF4\u1EF6\u1EF8\u1EFA\u1EFC\u1EFE"
|
||||
_latin_l_diacritics = r"\u1E01\u1E03\u1E05\u1E07\u1E09\u1E0B\u1E0D\u1E0F\u1E11\u1E13\u1E15\u1E17\u1E19\u1E1B" \
|
||||
r"\u1E1D\u1E1F\u1E21\u1E23\u1E25\u1E27\u1E29\u1E2B\u1E2D\u1E2F\u1E31\u1E33\u1E35\u1E37" \
|
||||
r"\u1E39\u1E3B\u1E3D\u1E3F\u1E41\u1E43\u1E45\u1E47\u1E49\u1E4B\u1E4D\u1E4F\u1E51\u1E53" \
|
||||
r"\u1E55\u1E57\u1E59\u1E5B\u1E5D\u1E5F\u1E61\u1E63\u1E65\u1E67\u1E69\u1E6B\u1E6D\u1E6F" \
|
||||
r"\u1E71\u1E73\u1E75\u1E77\u1E79\u1E7B\u1E7D\u1E7F\u1E81\u1E83\u1E85\u1E87\u1E89\u1E8B" \
|
||||
r"\u1E8D\u1E8F\u1E91\u1E93\u1E95-\u1E9D\u1E9F\u1EA1\u1EA3\u1EA5\u1EA7\u1EA9\u1EAB\u1EAD" \
|
||||
r"\u1EAF\u1EB1\u1EB3\u1EB5\u1EB7\u1EB9\u1EBB\u1EBD\u1EBF\u1EC1\u1EC3\u1EC5\u1EC7\u1EC9" \
|
||||
r"\u1ECB\u1ECD\u1ECF\u1ED1\u1ED3\u1ED5\u1ED7\u1ED9\u1EDB\u1EDD\u1EDF\u1EE1\u1EE3\u1EE5" \
|
||||
r"\u1EE7\u1EE9\u1EEB\u1EED\u1EEF\u1EF1\u1EF3\u1EF5\u1EF7\u1EF9\u1EFB\u1EFD\u1EFF"
|
||||
_latin_diacritics = r"\u1E00-\u1EFF"
|
||||
|
||||
# all lower latin classes
|
||||
LATIN_LOWER_BASIC = _latin_l_standard + _latin_l_standard_fullwidth + _latin_l_supplement + _latin_l_extendedA
|
||||
LATIN_LOWER = LATIN_LOWER_BASIC + _latin_l_extendedB + _latin_l_extendedC + _latin_l_extendedD + _latin_l_extendedE \
|
||||
+ _latin_l_phonetic + _latin_l_diacritics
|
||||
|
||||
# all upper latin classes
|
||||
LATIN_UPPER_BASIC = _latin_u_standard + _latin_u_standard_fullwidth + _latin_u_supplement + _latin_u_extendedA
|
||||
LATIN_UPPER = LATIN_UPPER_BASIC + _latin_u_extendedB + _latin_u_extendedC + _latin_u_extendedD + _latin_u_diacritics
|
||||
|
||||
# all latin classes
|
||||
LATIN_BASIC = _latin_standard + _latin_standard_fullwidth + _latin_supplement + _latin_extendedA
|
||||
LATIN = LATIN_BASIC + _latin_extendedB + _latin_extendedC + _latin_extendedD + _latin_extendedE \
|
||||
+ _latin_phonetic + _latin_diacritics
|
||||
|
||||
_persian = r"\u0620-\u064A\u066E-\u06D5\u06E5-\u06FF\u0750-\u077F\u08A0-\u08BD" \
|
||||
r"\uFB50-\uFBB1\uFBD3-\uFD3D\uFD50-\uFDC7\uFDF0-\uFDFB\uFE70-\uFEFC\U0001EE00-\U0001EEBB"
|
||||
|
||||
_russian_lower = r"ёа-я"
|
||||
_russian_upper = r"ЁА-Я"
|
||||
# \p{L}&&\p{Sinhala}
|
||||
_russian = r"ёа-яЁА-Я"
|
||||
|
||||
_sinhala = r"\u0D85-\u0D96\u0D9A-\u0DB1\u0DB3-\u0DBB\u0DBD\u0DC0-\u0DC6"
|
||||
|
||||
_tatar_lower = r"әөүҗңһ"
|
||||
_tatar_upper = r"ӘӨҮҖҢҺ"
|
||||
_tatar = r"әөүҗңһӘӨҮҖҢҺ"
|
||||
|
||||
_greek_lower = r"α-ωάέίόώήύ"
|
||||
_greek_upper = r"Α-ΩΆΈΊΌΏΉΎ"
|
||||
_greek = r"α-ωάέίόώήύΑ-ΩΆΈΊΌΏΉΎ"
|
||||
|
||||
_ukrainian_lower = r"а-щюяіїєґ"
|
||||
_ukrainian_upper = r"А-ЩЮЯІЇЄҐ"
|
||||
_ukrainian = r"а-щюяіїєґА-ЩЮЯІЇЄҐ"
|
||||
|
||||
_upper = LATIN_UPPER + _russian_upper + _tatar_upper + _greek_upper + _ukrainian_upper
|
||||
_lower = LATIN_LOWER + _russian_lower + _tatar_lower + _greek_lower + _ukrainian_lower
|
||||
|
||||
_upper = _latin_upper + _russian_upper + _tatar_upper + _greek_upper + _ukrainian_upper
|
||||
_lower = _latin_lower + _russian_lower + _tatar_lower + _greek_lower + _ukrainian_lower
|
||||
_uncased = _bengali + _hebrew + _persian + _sinhala
|
||||
|
||||
ALPHA = group_chars(_upper + _lower + _uncased)
|
||||
ALPHA = group_chars(LATIN + _russian + _tatar + _greek + _ukrainian + _uncased)
|
||||
ALPHA_LOWER = group_chars(_lower + _uncased)
|
||||
ALPHA_UPPER = group_chars(_upper + _uncased)
|
||||
|
||||
|
|
@ -63,7 +165,33 @@ _hyphens = "- – — -- --- —— ~"
|
|||
|
||||
# Various symbols like dingbats, but also emoji
|
||||
# Details: https://www.compart.com/en/unicode/category/So
|
||||
_other_symbols = r"\u00A6\u00A9\u00AE\u00B0\u0482\u058D\u058E\u060E\u060F\u06DE\u06E9\u06FD\u06FE\u07F6\u09FA\u0B70\u0BF3-\u0BF8\u0BFA\u0C7F\u0D4F\u0D79\u0F01-\u0F03\u0F13\u0F15-\u0F17\u0F1A-\u0F1F\u0F34\u0F36\u0F38\u0FBE-\u0FC5\u0FC7-\u0FCC\u0FCE\u0FCF\u0FD5-\u0FD8\u109E\u109F\u1390-\u1399\u1940\u19DE-\u19FF\u1B61-\u1B6A\u1B74-\u1B7C\u2100\u2101\u2103-\u2106\u2108\u2109\u2114\u2116\u2117\u211E-\u2123\u2125\u2127\u2129\u212E\u213A\u213B\u214A\u214C\u214D\u214F\u218A\u218B\u2195-\u2199\u219C-\u219F\u21A1\u21A2\u21A4\u21A5\u21A7-\u21AD\u21AF-\u21CD\u21D0\u21D1\u21D3\u21D5-\u21F3\u2300-\u2307\u230C-\u231F\u2322-\u2328\u232B-\u237B\u237D-\u239A\u23B4-\u23DB\u23E2-\u2426\u2440-\u244A\u249C-\u24E9\u2500-\u25B6\u25B8-\u25C0\u25C2-\u25F7\u2600-\u266E\u2670-\u2767\u2794-\u27BF\u2800-\u28FF\u2B00-\u2B2F\u2B45\u2B46\u2B4D-\u2B73\u2B76-\u2B95\u2B98-\u2BC8\u2BCA-\u2BFE\u2CE5-\u2CEA\u2E80-\u2E99\u2E9B-\u2EF3\u2F00-\u2FD5\u2FF0-\u2FFB\u3004\u3012\u3013\u3020\u3036\u3037\u303E\u303F\u3190\u3191\u3196-\u319F\u31C0-\u31E3\u3200-\u321E\u322A-\u3247\u3250\u3260-\u327F\u328A-\u32B0\u32C0-\u32FE\u3300-\u33FF\u4DC0-\u4DFF\uA490-\uA4C6\uA828-\uA82B\uA836\uA837\uA839\uAA77-\uAA79\uFDFD\uFFE4\uFFE8\uFFED\uFFEE\uFFFC\uFFFD\U00010137-\U0001013F\U00010179-\U00010189\U0001018C-\U0001018E\U00010190-\U0001019B\U000101A0\U000101D0-\U000101FC\U00010877\U00010878\U00010AC8\U0001173F\U00016B3C-\U00016B3F\U00016B45\U0001BC9C\U0001D000-\U0001D0F5\U0001D100-\U0001D126\U0001D129-\U0001D164\U0001D16A-\U0001D16C\U0001D183\U0001D184\U0001D18C-\U0001D1A9\U0001D1AE-\U0001D1E8\U0001D200-\U0001D241\U0001D245\U0001D300-\U0001D356\U0001D800-\U0001D9FF\U0001DA37-\U0001DA3A\U0001DA6D-\U0001DA74\U0001DA76-\U0001DA83\U0001DA85\U0001DA86\U0001ECAC\U0001F000-\U0001F02B\U0001F030-\U0001F093\U0001F0A0-\U0001F0AE\U0001F0B1-\U0001F0BF\U0001F0C1-\U0001F0CF\U0001F0D1-\U0001F0F5\U0001F110-\U0001F16B\U0001F170-\U0001F1AC\U0001F1E6-\U0001F202\U0001F210-\U0001F23B\U0001F240-\U0001F248\U0001F250\U0001F251\U0001F260-\U0001F265\U0001F300-\U0001F3FA\U0001F400-\U0001F6D4\U0001F6E0-\U0001F6EC\U0001F6F0-\U0001F6F9\U0001F700-\U0001F773\U0001F780-\U0001F7D8\U0001F800-\U0001F80B\U0001F810-\U0001F847\U0001F850-\U0001F859\U0001F860-\U0001F887\U0001F890-\U0001F8AD\U0001F900-\U0001F90B\U0001F910-\U0001F93E\U0001F940-\U0001F970\U0001F973-\U0001F976\U0001F97A\U0001F97C-\U0001F9A2\U0001F9B0-\U0001F9B9\U0001F9C0-\U0001F9C2\U0001F9D0-\U0001F9FF\U0001FA60-\U0001FA6D"
|
||||
_other_symbols = r"\u00A6\u00A9\u00AE\u00B0\u0482\u058D\u058E\u060E\u060F\u06DE\u06E9\u06FD\u06FE\u07F6\u09FA\u0B70" \
|
||||
r"\u0BF3-\u0BF8\u0BFA\u0C7F\u0D4F\u0D79\u0F01-\u0F03\u0F13\u0F15-\u0F17\u0F1A-\u0F1F\u0F34" \
|
||||
r"\u0F36\u0F38\u0FBE-\u0FC5\u0FC7-\u0FCC\u0FCE\u0FCF\u0FD5-\u0FD8\u109E\u109F\u1390-\u1399" \
|
||||
r"\u1940\u19DE-\u19FF\u1B61-\u1B6A\u1B74-\u1B7C\u2100\u2101\u2103-\u2106\u2108\u2109\u2114\u2116" \
|
||||
r"\u2117\u211E-\u2123\u2125\u2127\u2129\u212E\u213A\u213B\u214A\u214C\u214D\u214F\u218A\u218B" \
|
||||
r"\u2195-\u2199\u219C-\u219F\u21A1\u21A2\u21A4\u21A5\u21A7-\u21AD\u21AF-\u21CD\u21D0\u21D1\u21D3" \
|
||||
r"\u21D5-\u21F3\u2300-\u2307\u230C-\u231F\u2322-\u2328\u232B-\u237B\u237D-\u239A\u23B4-\u23DB" \
|
||||
r"\u23E2-\u2426\u2440-\u244A\u249C-\u24E9\u2500-\u25B6\u25B8-\u25C0\u25C2-\u25F7\u2600-\u266E" \
|
||||
r"\u2670-\u2767\u2794-\u27BF\u2800-\u28FF\u2B00-\u2B2F\u2B45\u2B46\u2B4D-\u2B73\u2B76-\u2B95" \
|
||||
r"\u2B98-\u2BC8\u2BCA-\u2BFE\u2CE5-\u2CEA\u2E80-\u2E99\u2E9B-\u2EF3\u2F00-\u2FD5\u2FF0-\u2FFB" \
|
||||
r"\u3004\u3012\u3013\u3020\u3036\u3037\u303E\u303F\u3190\u3191\u3196-\u319F\u31C0-\u31E3" \
|
||||
r"\u3200-\u321E\u322A-\u3247\u3250\u3260-\u327F\u328A-\u32B0\u32C0-\u32FE\u3300-\u33FF\u4DC0-\u4DFF" \
|
||||
r"\uA490-\uA4C6\uA828-\uA82B\uA836\uA837\uA839\uAA77-\uAA79\uFDFD\uFFE4\uFFE8\uFFED\uFFEE\uFFFC" \
|
||||
r"\uFFFD\U00010137-\U0001013F\U00010179-\U00010189\U0001018C-\U0001018E\U00010190-\U0001019B" \
|
||||
r"\U000101A0\U000101D0-\U000101FC\U00010877\U00010878\U00010AC8\U0001173F\U00016B3C-\U00016B3F" \
|
||||
r"\U00016B45\U0001BC9C\U0001D000-\U0001D0F5\U0001D100-\U0001D126\U0001D129-\U0001D164" \
|
||||
r"\U0001D16A-\U0001D16C\U0001D183\U0001D184\U0001D18C-\U0001D1A9\U0001D1AE-\U0001D1E8" \
|
||||
r"\U0001D200-\U0001D241\U0001D245\U0001D300-\U0001D356\U0001D800-\U0001D9FF\U0001DA37-\U0001DA3A" \
|
||||
r"\U0001DA6D-\U0001DA74\U0001DA76-\U0001DA83\U0001DA85\U0001DA86\U0001ECAC\U0001F000-\U0001F02B" \
|
||||
r"\U0001F030-\U0001F093\U0001F0A0-\U0001F0AE\U0001F0B1-\U0001F0BF\U0001F0C1-\U0001F0CF" \
|
||||
r"\U0001F0D1-\U0001F0F5\U0001F110-\U0001F16B\U0001F170-\U0001F1AC\U0001F1E6-\U0001F202" \
|
||||
r"\U0001F210-\U0001F23B\U0001F240-\U0001F248\U0001F250\U0001F251\U0001F260-\U0001F265" \
|
||||
r"\U0001F300-\U0001F3FA\U0001F400-\U0001F6D4\U0001F6E0-\U0001F6EC\U0001F6F0-\U0001F6F9" \
|
||||
r"\U0001F700-\U0001F773\U0001F780-\U0001F7D8\U0001F800-\U0001F80B\U0001F810-\U0001F847" \
|
||||
r"\U0001F850-\U0001F859\U0001F860-\U0001F887\U0001F890-\U0001F8AD\U0001F900-\U0001F90B" \
|
||||
r"\U0001F910-\U0001F93E\U0001F940-\U0001F970\U0001F973-\U0001F976\U0001F97A\U0001F97C-\U0001F9A2" \
|
||||
r"\U0001F9B0-\U0001F9B9\U0001F9C0-\U0001F9C2\U0001F9D0-\U0001F9FF\U0001FA60-\U0001FA6D"
|
||||
|
||||
UNITS = merge_chars(_units)
|
||||
CURRENCY = merge_chars(_currency)
|
||||
|
|
|
|||
|
|
@ -7076,14 +7076,6 @@ FR_BASE_EXCEPTIONS = [
|
|||
"au-lof",
|
||||
"au-tour",
|
||||
"aube-vigne",
|
||||
"audio-numérique",
|
||||
"audio-numériques",
|
||||
"audio-prothésiste",
|
||||
"audio-prothésistes",
|
||||
"audio-visuel",
|
||||
"audio-visuelle",
|
||||
"audio-visuelles",
|
||||
"audio-visuels",
|
||||
"aujourd'hui",
|
||||
"aulnaie-frênaie",
|
||||
"aulnaies-frênaies",
|
||||
|
|
@ -14400,7 +14392,6 @@ FR_BASE_EXCEPTIONS = [
|
|||
"attaques surprises",
|
||||
"attaques-surprises",
|
||||
"attrape-con",
|
||||
"audio-oral",
|
||||
"auriculo-cardiaque",
|
||||
"auriculo-temporal",
|
||||
"austro-bavarois",
|
||||
|
|
|
|||
|
|
@ -3,12 +3,15 @@ from __future__ import unicode_literals
|
|||
|
||||
import re
|
||||
|
||||
from ._tokenizer_exceptions_list import FR_BASE_EXCEPTIONS
|
||||
from .punctuation import ELISION, HYPHENS
|
||||
from ..tokenizer_exceptions import URL_PATTERN
|
||||
from ..char_classes import ALPHA_LOWER, ALPHA
|
||||
from ...symbols import ORTH, LEMMA, TAG
|
||||
|
||||
# not using the large _tokenizer_exceptions_list by default as it slows down the tokenizer
|
||||
# from ._tokenizer_exceptions_list import FR_BASE_EXCEPTIONS
|
||||
FR_BASE_EXCEPTIONS = ["aujourd'hui", "Aujourd'hui"]
|
||||
|
||||
|
||||
def upper_first_letter(text):
|
||||
if len(text) == 0:
|
||||
|
|
@ -128,6 +131,7 @@ _hyphen_prefix = [
|
|||
"arcs?",
|
||||
"archi",
|
||||
"arrières?",
|
||||
"audio",
|
||||
"avant",
|
||||
"avion",
|
||||
"auto",
|
||||
|
|
|
|||
|
|
@ -636,17 +636,17 @@ for orth in [
|
|||
_exc[orth] = [{ORTH: orth}]
|
||||
|
||||
|
||||
_ord_num_or_date = "([A-Z0-9]+[./-])*(\d+\.?)"
|
||||
_num = "[+\-]?\d+([,.]\d+)*"
|
||||
_ops = "[=<>+\-\*/^()÷%²]"
|
||||
_suffixes = "-[{al}]+".format(al=ALPHA_LOWER)
|
||||
_numeric_exp = "({n})(({o})({n}))*[%]?".format(n=_num, o=_ops)
|
||||
_time_exp = "\d+(:\d+)*(\.\d+)?"
|
||||
_ord_num_or_date = r"([A-Z0-9]+[./-])*(\d+\.?)"
|
||||
_num = r"[+\-]?\d+([,.]\d+)*"
|
||||
_ops = r"[=<>+\-\*/^()÷%²]"
|
||||
_suffixes = r"-[{al}]+".format(al=ALPHA_LOWER)
|
||||
_numeric_exp = r"({n})(({o})({n}))*[%]?".format(n=_num, o=_ops)
|
||||
_time_exp = r"\d+(:\d+)*(\.\d+)?"
|
||||
|
||||
_nums = "(({ne})|({t})|({on})|({c}))({s})?".format(
|
||||
_nums = r"(({ne})|({t})|({on})|({c}))({s})?".format(
|
||||
ne=_numeric_exp, t=_time_exp, on=_ord_num_or_date, c=CURRENCY, s=_suffixes
|
||||
)
|
||||
|
||||
|
||||
TOKENIZER_EXCEPTIONS = _exc
|
||||
TOKEN_MATCH = re.compile("^({u})|({n})$".format(u=URL_PATTERN, n=_nums)).match
|
||||
TOKEN_MATCH = re.compile(r"^({u})|({n})$".format(u=URL_PATTERN, n=_nums)).match
|
||||
|
|
|
|||
|
|
@ -4,6 +4,7 @@ from __future__ import unicode_literals
|
|||
from .stop_words import STOP_WORDS
|
||||
from .lemmatizer import LOOKUP
|
||||
from .tag_map import TAG_MAP
|
||||
from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
|
||||
|
||||
from ..tokenizer_exceptions import BASE_EXCEPTIONS
|
||||
from ..norm_exceptions import BASE_NORMS
|
||||
|
|
@ -20,7 +21,7 @@ class ItalianDefaults(Language.Defaults):
|
|||
lex_attr_getters[NORM] = add_lookups(
|
||||
Language.Defaults.lex_attr_getters[NORM], BASE_NORMS
|
||||
)
|
||||
tokenizer_exceptions = update_exc(BASE_EXCEPTIONS)
|
||||
tokenizer_exceptions = update_exc(BASE_EXCEPTIONS, TOKENIZER_EXCEPTIONS)
|
||||
stop_words = STOP_WORDS
|
||||
lemma_lookup = LOOKUP
|
||||
tag_map = TAG_MAP
|
||||
|
|
|
|||
9
spacy/lang/it/tokenizer_exceptions.py
Normal file
9
spacy/lang/it/tokenizer_exceptions.py
Normal file
|
|
@ -0,0 +1,9 @@
|
|||
# coding: utf8
|
||||
from __future__ import unicode_literals
|
||||
from ...symbols import ORTH, LEMMA
|
||||
|
||||
_exc = {
|
||||
"po'": [{ORTH: "po'", LEMMA: 'poco'}]
|
||||
}
|
||||
|
||||
TOKENIZER_EXCEPTIONS = _exc
|
||||
|
|
@ -39,10 +39,10 @@ _infixes = (
|
|||
+ LIST_ICONS
|
||||
+ [
|
||||
r"(?<=[0-9])[+\-\*^](?=[0-9-])",
|
||||
r"(?<=[{al}])\.(?=[{au}])".format(al=ALPHA_LOWER, au=ALPHA_UPPER),
|
||||
r"(?<=[{al}{q}])\.(?=[{au}{q}])".format(al=ALPHA_LOWER, au=ALPHA_UPPER, q=CONCAT_QUOTES),
|
||||
r"(?<=[{a}]),(?=[{a}])".format(a=ALPHA),
|
||||
r"(?<=[{a}])(?:{h})(?=[{a}])".format(a=ALPHA, h=HYPHENS),
|
||||
r"(?<=[{a}])[:<>=/](?=[{a}])".format(a=ALPHA),
|
||||
r"(?<=[{a}0-9])[:<>=/](?=[{a}])".format(a=ALPHA),
|
||||
]
|
||||
)
|
||||
|
||||
|
|
|
|||
|
|
@ -44,7 +44,7 @@ cdef find_matches(TokenPatternC** patterns, int n, Doc doc, extensions=None,
|
|||
cdef Pool mem = Pool()
|
||||
predicate_cache = <char*>mem.alloc(doc.length * len(predicates), sizeof(char))
|
||||
if extensions is not None and len(extensions) >= 1:
|
||||
nr_extra_attr = max(extensions.values())
|
||||
nr_extra_attr = max(extensions.values()) + 1
|
||||
extra_attr_values = <attr_t*>mem.alloc(doc.length * nr_extra_attr, sizeof(attr_t))
|
||||
else:
|
||||
nr_extra_attr = 0
|
||||
|
|
@ -60,9 +60,8 @@ cdef find_matches(TokenPatternC** patterns, int n, Doc doc, extensions=None,
|
|||
for i in range(doc.length):
|
||||
for j in range(n):
|
||||
states.push_back(PatternStateC(patterns[j], i, 0))
|
||||
transition_states(states, matches, predicate_cache,
|
||||
transition_states(states, matches, &predicate_cache[i],
|
||||
doc[i], extra_attr_values, predicates)
|
||||
predicate_cache += nr_predicate
|
||||
extra_attr_values += nr_extra_attr
|
||||
# Handle matches that end in 0-width patterns
|
||||
finish_states(matches, states)
|
||||
|
|
@ -74,6 +73,7 @@ cdef find_matches(TokenPatternC** patterns, int n, Doc doc, extensions=None,
|
|||
matches[i].start,
|
||||
matches[i].start+matches[i].length
|
||||
)
|
||||
|
||||
# We need to deduplicate, because we could otherwise arrive at the same
|
||||
# match through two paths, e.g. .?.? matching 'a'. Are we matching the
|
||||
# first .?, or the second .? -- it doesn't matter, it's just one match.
|
||||
|
|
@ -89,7 +89,8 @@ cdef attr_t get_ent_id(const TokenPatternC* pattern) nogil:
|
|||
# showed this wasn't the case when we had a reject-and-continue before a
|
||||
# match. I still don't really understand what's going on here, but this
|
||||
# workaround does resolve the issue.
|
||||
while pattern.attrs.attr != ID and pattern.nr_attr > 0:
|
||||
while pattern.attrs.attr != ID and \
|
||||
(pattern.nr_attr > 0 or pattern.nr_extra_attr > 0 or pattern.nr_py > 0):
|
||||
pattern += 1
|
||||
return pattern.attrs.value
|
||||
|
||||
|
|
@ -101,13 +102,17 @@ cdef void transition_states(vector[PatternStateC]& states, vector[MatchC]& match
|
|||
cdef vector[PatternStateC] new_states
|
||||
cdef int nr_predicate = len(py_predicates)
|
||||
for i in range(states.size()):
|
||||
if states[i].pattern.nr_py != 0:
|
||||
if states[i].pattern.nr_py >= 1:
|
||||
update_predicate_cache(cached_py_predicates,
|
||||
states[i].pattern, token, py_predicates)
|
||||
for i in range(states.size()):
|
||||
action = get_action(states[i], token.c, extra_attrs,
|
||||
cached_py_predicates, nr_predicate)
|
||||
cached_py_predicates)
|
||||
if action == REJECT:
|
||||
continue
|
||||
# Keep only a subset of states (the active ones). Index q is the
|
||||
# states which are still alive. If we reject a state, we overwrite
|
||||
# it in the states list, because q doesn't advance.
|
||||
state = states[i]
|
||||
states[q] = state
|
||||
while action in (RETRY, RETRY_ADVANCE, RETRY_EXTEND):
|
||||
|
|
@ -126,7 +131,7 @@ cdef void transition_states(vector[PatternStateC]& states, vector[MatchC]& match
|
|||
update_predicate_cache(cached_py_predicates,
|
||||
states[q].pattern, token, py_predicates)
|
||||
action = get_action(states[q], token.c, extra_attrs,
|
||||
cached_py_predicates, nr_predicate)
|
||||
cached_py_predicates)
|
||||
if action == REJECT:
|
||||
pass
|
||||
elif action == ADVANCE:
|
||||
|
|
@ -154,8 +159,8 @@ cdef void transition_states(vector[PatternStateC]& states, vector[MatchC]& match
|
|||
states.push_back(new_states[i])
|
||||
|
||||
|
||||
cdef void update_predicate_cache(char* cache,
|
||||
const TokenPatternC* pattern, Token token, predicates):
|
||||
cdef int update_predicate_cache(char* cache,
|
||||
const TokenPatternC* pattern, Token token, predicates) except -1:
|
||||
# If the state references any extra predicates, check whether they match.
|
||||
# These are cached, so that we don't call these potentially expensive
|
||||
# Python functions more than we need to.
|
||||
|
|
@ -192,7 +197,7 @@ cdef void finish_states(vector[MatchC]& matches, vector[PatternStateC]& states)
|
|||
|
||||
cdef action_t get_action(PatternStateC state,
|
||||
const TokenC* token, const attr_t* extra_attrs,
|
||||
const char* predicate_matches, int nr_predicate) nogil:
|
||||
const char* predicate_matches) nogil:
|
||||
'''We need to consider:
|
||||
|
||||
a) Does the token match the specification? [Yes, No]
|
||||
|
|
@ -252,7 +257,7 @@ cdef action_t get_action(PatternStateC state,
|
|||
Problem: If a quantifier is matching, we're adding a lot of open partials
|
||||
'''
|
||||
cdef char is_match
|
||||
is_match = get_is_match(state, token, extra_attrs, predicate_matches, nr_predicate)
|
||||
is_match = get_is_match(state, token, extra_attrs, predicate_matches)
|
||||
quantifier = get_quantifier(state)
|
||||
is_final = get_is_final(state)
|
||||
if quantifier == ZERO:
|
||||
|
|
@ -303,9 +308,9 @@ cdef action_t get_action(PatternStateC state,
|
|||
|
||||
cdef char get_is_match(PatternStateC state,
|
||||
const TokenC* token, const attr_t* extra_attrs,
|
||||
const char* predicate_matches, int nr_predicate) nogil:
|
||||
for i in range(nr_predicate):
|
||||
if predicate_matches[i] == -1:
|
||||
const char* predicate_matches) nogil:
|
||||
for i in range(state.pattern.nr_py):
|
||||
if predicate_matches[state.pattern.py_predicates[i]] == -1:
|
||||
return 0
|
||||
spec = state.pattern
|
||||
for attr in spec.attrs[:spec.nr_attr]:
|
||||
|
|
@ -333,7 +338,7 @@ DEF PADDING = 5
|
|||
|
||||
cdef TokenPatternC* init_pattern(Pool mem, attr_t entity_id, object token_specs) except NULL:
|
||||
pattern = <TokenPatternC*>mem.alloc(len(token_specs) + 1, sizeof(TokenPatternC))
|
||||
cdef int i
|
||||
cdef int i, index
|
||||
for i, (quantifier, spec, extensions, predicates) in enumerate(token_specs):
|
||||
pattern[i].quantifier = quantifier
|
||||
pattern[i].attrs = <AttrValueC*>mem.alloc(len(spec), sizeof(AttrValueC))
|
||||
|
|
@ -356,11 +361,13 @@ cdef TokenPatternC* init_pattern(Pool mem, attr_t entity_id, object token_specs)
|
|||
pattern[i].attrs[0].attr = ID
|
||||
pattern[i].attrs[0].value = entity_id
|
||||
pattern[i].nr_attr = 0
|
||||
pattern[i].nr_extra_attr = 0
|
||||
pattern[i].nr_py = 0
|
||||
return pattern
|
||||
|
||||
|
||||
cdef attr_t get_pattern_key(const TokenPatternC* pattern) nogil:
|
||||
while pattern.nr_attr != 0:
|
||||
while pattern.nr_attr != 0 or pattern.nr_extra_attr != 0 or pattern.nr_py != 0:
|
||||
pattern += 1
|
||||
id_attr = pattern[0].attrs[0]
|
||||
if id_attr.attr != ID:
|
||||
|
|
@ -384,7 +391,6 @@ def _preprocess_pattern(token_specs, string_store, extensions_table, extra_predi
|
|||
extra_predicates.
|
||||
"""
|
||||
tokens = []
|
||||
seen_predicates = {}
|
||||
for spec in token_specs:
|
||||
if not spec:
|
||||
# Signifier for 'any token'
|
||||
|
|
@ -393,7 +399,7 @@ def _preprocess_pattern(token_specs, string_store, extensions_table, extra_predi
|
|||
ops = _get_operators(spec)
|
||||
attr_values = _get_attr_values(spec, string_store)
|
||||
extensions = _get_extensions(spec, string_store, extensions_table)
|
||||
predicates = _get_extra_predicates(spec, extra_predicates, seen_predicates)
|
||||
predicates = _get_extra_predicates(spec, extra_predicates)
|
||||
for op in ops:
|
||||
tokens.append((op, list(attr_values), list(extensions), list(predicates)))
|
||||
return tokens
|
||||
|
|
@ -430,6 +436,7 @@ class _RegexPredicate(object):
|
|||
self.value = re.compile(value)
|
||||
self.predicate = predicate
|
||||
self.is_extension = is_extension
|
||||
self.key = (attr, self.predicate, srsly.json_dumps(value, sort_keys=True))
|
||||
assert self.predicate == 'REGEX'
|
||||
|
||||
def __call__(self, Token token):
|
||||
|
|
@ -447,6 +454,7 @@ class _SetMemberPredicate(object):
|
|||
self.value = set(get_string_id(v) for v in value)
|
||||
self.predicate = predicate
|
||||
self.is_extension = is_extension
|
||||
self.key = (attr, self.predicate, srsly.json_dumps(value, sort_keys=True))
|
||||
assert self.predicate in ('IN', 'NOT_IN')
|
||||
|
||||
def __call__(self, Token token):
|
||||
|
|
@ -459,6 +467,9 @@ class _SetMemberPredicate(object):
|
|||
else:
|
||||
return value not in self.value
|
||||
|
||||
def __repr__(self):
|
||||
return repr(('SetMemberPredicate', self.i, self.attr, self.value, self.predicate))
|
||||
|
||||
|
||||
class _ComparisonPredicate(object):
|
||||
def __init__(self, i, attr, value, predicate, is_extension=False):
|
||||
|
|
@ -467,6 +478,7 @@ class _ComparisonPredicate(object):
|
|||
self.value = value
|
||||
self.predicate = predicate
|
||||
self.is_extension = is_extension
|
||||
self.key = (attr, self.predicate, srsly.json_dumps(value, sort_keys=True))
|
||||
assert self.predicate in ('==', '!=', '>=', '<=', '>', '<')
|
||||
|
||||
def __call__(self, Token token):
|
||||
|
|
@ -488,7 +500,7 @@ class _ComparisonPredicate(object):
|
|||
return value < self.value
|
||||
|
||||
|
||||
def _get_extra_predicates(spec, extra_predicates, seen_predicates):
|
||||
def _get_extra_predicates(spec, extra_predicates):
|
||||
predicate_types = {
|
||||
'REGEX': _RegexPredicate,
|
||||
'IN': _SetMemberPredicate,
|
||||
|
|
@ -499,6 +511,7 @@ def _get_extra_predicates(spec, extra_predicates, seen_predicates):
|
|||
'>': _ComparisonPredicate,
|
||||
'<': _ComparisonPredicate,
|
||||
}
|
||||
seen_predicates = {pred.key: pred.i for pred in extra_predicates}
|
||||
output = []
|
||||
for attr, value in spec.items():
|
||||
if isinstance(attr, basestring):
|
||||
|
|
@ -516,16 +529,15 @@ def _get_extra_predicates(spec, extra_predicates, seen_predicates):
|
|||
if isinstance(value, dict):
|
||||
for type_, cls in predicate_types.items():
|
||||
if type_ in value:
|
||||
key = (attr, type_, srsly.json_dumps(value[type_], sort_keys=True))
|
||||
predicate = cls(len(extra_predicates), attr, value[type_], type_)
|
||||
# Don't create a redundant predicates.
|
||||
# This helps with efficiency, as we're caching the results.
|
||||
if key in seen_predicates:
|
||||
output.append(seen_predicates[key])
|
||||
if predicate.key in seen_predicates:
|
||||
output.append(seen_predicates[predicate.key])
|
||||
else:
|
||||
predicate = cls(len(extra_predicates), attr, value[type_], type_)
|
||||
extra_predicates.append(predicate)
|
||||
output.append(predicate.i)
|
||||
seen_predicates[key] = predicate.i
|
||||
seen_predicates[predicate.key] = predicate.i
|
||||
return output
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -145,9 +145,7 @@ class Pipe(object):
|
|||
"""Serialize the pipe to a bytestring."""
|
||||
serialize = OrderedDict()
|
||||
serialize["cfg"] = lambda: srsly.json_dumps(self.cfg)
|
||||
if self.model in (True, False, None):
|
||||
serialize["model"] = lambda: self.model
|
||||
else:
|
||||
if self.model not in (True, False, None):
|
||||
serialize["model"] = self.model.to_bytes
|
||||
serialize["vocab"] = self.vocab.to_bytes
|
||||
return util.to_bytes(serialize, exclude)
|
||||
|
|
@ -538,9 +536,7 @@ class Tagger(Pipe):
|
|||
|
||||
def to_bytes(self, **exclude):
|
||||
serialize = OrderedDict()
|
||||
if self.model in (None, True, False):
|
||||
serialize['model'] = lambda: self.model
|
||||
else:
|
||||
if self.model not in (None, True, False):
|
||||
serialize['model'] = self.model.to_bytes
|
||||
serialize['vocab'] = self.vocab.to_bytes
|
||||
serialize['cfg'] = lambda: srsly.json_dumps(self.cfg)
|
||||
|
|
|
|||
|
|
@ -261,13 +261,14 @@ class ParserStepModel(Model):
|
|||
# lowest score.
|
||||
# numpy's nan_to_num function doesn't take a value, and nan is replaced
|
||||
# by 0...-inf is replaced by minimum, so we go via that. Ugly to the max.
|
||||
scores[self.ops.xp.isnan(scores)] = -self.ops.xp.inf
|
||||
self.ops.xp.nan_to_num(scores, copy=False)
|
||||
# Note that scores is always a numpy array! Should fix #3112
|
||||
scores[numpy.isnan(scores)] = -numpy.inf
|
||||
numpy.nan_to_num(scores, copy=False)
|
||||
|
||||
def backprop_parser_step(d_scores, sgd=None):
|
||||
# If we have a non-zero gradient for a previously unseen class,
|
||||
# replace the weight with 0.
|
||||
new_classes = self.ops.xp.logical_and(
|
||||
new_classes = self.vec2scores.ops.xp.logical_and(
|
||||
self.vec2scores.ops.xp.isnan(self.vec2scores.b),
|
||||
d_scores.any(axis=0)
|
||||
)
|
||||
|
|
|
|||
|
|
@ -13,10 +13,10 @@ def custom_en_tokenizer(en_vocab):
|
|||
prefix_re = compile_prefix_regex(English.Defaults.prefixes)
|
||||
suffix_re = compile_suffix_regex(English.Defaults.suffixes)
|
||||
custom_infixes = [
|
||||
"\.\.\.+",
|
||||
"(?<=[0-9])-(?=[0-9])",
|
||||
"[0-9]+(,[0-9]+)+",
|
||||
"[\[\]!&:,()\*—–\/-]",
|
||||
r"\.\.\.+",
|
||||
r"(?<=[0-9])-(?=[0-9])",
|
||||
r"[0-9]+(,[0-9]+)+",
|
||||
r"[\[\]!&:,()\*—–\/-]",
|
||||
]
|
||||
infix_re = compile_infix_regex(custom_infixes)
|
||||
return Tokenizer(
|
||||
|
|
|
|||
|
|
@ -22,9 +22,9 @@ import pytest
|
|||
u"11-septembre",
|
||||
u"11-Septembre",
|
||||
u"refox-trottâmes",
|
||||
u"K-POP",
|
||||
u"K-Pop",
|
||||
u"K-pop",
|
||||
# u"K-POP",
|
||||
# u"K-Pop",
|
||||
# u"K-pop",
|
||||
u"z'yeutes",
|
||||
u"black-outeront",
|
||||
u"états-unienne",
|
||||
|
|
|
|||
|
|
@ -207,14 +207,13 @@ def test_matcher_set_value(en_vocab):
|
|||
assert len(matches) == 0
|
||||
|
||||
|
||||
@pytest.mark.xfail
|
||||
def test_matcher_set_value_operator(en_vocab):
|
||||
matcher = Matcher(en_vocab)
|
||||
pattern = [{"ORTH": {"IN": ["a", "the"]}, "OP": "?"}, {"ORTH": "house"}]
|
||||
matcher.add("DET_HOUSE", None, pattern)
|
||||
doc = Doc(en_vocab, words=["In", "a", "house"])
|
||||
matches = matcher(doc)
|
||||
assert len(matches) == 1
|
||||
assert len(matches) == 2
|
||||
doc = Doc(en_vocab, words=["my", "house"])
|
||||
matches = matcher(doc)
|
||||
assert len(matches) == 1
|
||||
|
|
|
|||
|
|
@ -358,6 +358,7 @@ def test_issue850_basic():
|
|||
assert end == 4
|
||||
|
||||
|
||||
@pytest.mark.skip(reason="French exception list is not enabled in the default tokenizer anymore")
|
||||
@pytest.mark.parametrize(
|
||||
"text", ["au-delàs", "pair-programmâmes", "terra-formées", "σ-compacts"]
|
||||
)
|
||||
|
|
|
|||
|
|
@ -13,6 +13,22 @@ from spacy.lemmatizer import Lemmatizer
|
|||
from spacy.symbols import ORTH, LEMMA, POS, VERB, VerbForm_part
|
||||
|
||||
|
||||
@pytest.mark.xfail(
|
||||
reason="g is split of as a unit, as the suffix regular expression can not look back further (variable-width)"
|
||||
)
|
||||
def test_issue1235():
|
||||
"""Test that g is not split of if preceded by a number and a letter"""
|
||||
nlp = English()
|
||||
testwords = u'e2g 2g 52g'
|
||||
doc = nlp(testwords)
|
||||
assert len(doc) == 5
|
||||
assert doc[0].text == "e2g"
|
||||
assert doc[1].text == "2"
|
||||
assert doc[2].text == "g"
|
||||
assert doc[3].text == "52"
|
||||
assert doc[4].text == "g"
|
||||
|
||||
|
||||
def test_issue1242():
|
||||
nlp = English()
|
||||
doc = nlp("")
|
||||
|
|
|
|||
|
|
@ -6,7 +6,6 @@ from spacy.matcher import Matcher
|
|||
from spacy.tokens import Token, Doc
|
||||
|
||||
|
||||
@pytest.mark.xfail
|
||||
def test_issue1971(en_vocab):
|
||||
# Possibly related to #2675 and #2671?
|
||||
matcher = Matcher(en_vocab)
|
||||
|
|
@ -22,21 +21,20 @@ def test_issue1971(en_vocab):
|
|||
# We could also assert length 1 here, but this is more conclusive, because
|
||||
# the real problem here is that it returns a duplicate match for a match_id
|
||||
# that's not actually in the vocab!
|
||||
assert all(match_id in en_vocab.strings for match_id, start, end in matcher(doc))
|
||||
matches = matcher(doc)
|
||||
assert all([match_id in en_vocab.strings for match_id, start, end in matches])
|
||||
|
||||
|
||||
@pytest.mark.xfail
|
||||
def test_issue_1971_2(en_vocab):
|
||||
matcher = Matcher(en_vocab)
|
||||
pattern1 = [{"LOWER": {"IN": ["eur"]}}, {"LIKE_NUM": True}]
|
||||
pattern2 = list(reversed(pattern1))
|
||||
pattern1 = [{"ORTH": "EUR", "LOWER": {"IN": ["eur"]}}, {"LIKE_NUM": True}]
|
||||
pattern2 = [{"LIKE_NUM": True}, {"ORTH": "EUR"}] #{"IN": ["EUR"]}}]
|
||||
doc = Doc(en_vocab, words=["EUR", "10", "is", "10", "EUR"])
|
||||
matcher.add("TEST", None, pattern1, pattern2)
|
||||
matcher.add("TEST1", None, pattern1, pattern2)
|
||||
matches = matcher(doc)
|
||||
assert len(matches) == 2
|
||||
|
||||
|
||||
@pytest.mark.xfail
|
||||
def test_issue_1971_3(en_vocab):
|
||||
"""Test that pattern matches correctly for multiple extension attributes."""
|
||||
Token.set_extension("a", default=1)
|
||||
|
|
@ -50,7 +48,6 @@ def test_issue_1971_3(en_vocab):
|
|||
assert matches == sorted([("A", 0, 1), ("A", 1, 2), ("B", 0, 1), ("B", 1, 2)])
|
||||
|
||||
|
||||
# @pytest.mark.xfail
|
||||
def test_issue_1971_4(en_vocab):
|
||||
"""Test that pattern matches correctly with multiple extension attribute
|
||||
values on a single token.
|
||||
|
|
|
|||
|
|
@ -7,10 +7,22 @@ from spacy.displacy import render
|
|||
from spacy.gold import iob_to_biluo
|
||||
from spacy.lang.it import Italian
|
||||
import numpy
|
||||
from spacy.lang.en import English
|
||||
|
||||
from ..util import add_vecs_to_vocab, get_doc
|
||||
|
||||
|
||||
@pytest.mark.xfail(
|
||||
reason="The dot is now properly split off, but the prefix/suffix rules are not applied again afterwards."
|
||||
"This means that the quote will still be attached to the remaining token."
|
||||
)
|
||||
def test_issue2070():
|
||||
"""Test that checks that a dot followed by a quote is handled appropriately."""
|
||||
nlp = English()
|
||||
doc = nlp('First sentence."A quoted sentence" he said ...')
|
||||
assert len(doc) == 11
|
||||
|
||||
|
||||
def test_issue2179():
|
||||
"""Test that spurious 'extra_labels' aren't created when initializing NER."""
|
||||
nlp = Italian()
|
||||
|
|
|
|||
24
spacy/tests/regression/test_issue2656.py
Normal file
24
spacy/tests/regression/test_issue2656.py
Normal file
|
|
@ -0,0 +1,24 @@
|
|||
# coding: utf8
|
||||
from __future__ import unicode_literals
|
||||
from spacy.lang.en import English
|
||||
|
||||
|
||||
def test_issue2656():
|
||||
""" Test that tokenizer correctly splits of punctuation after numbers with decimal points """
|
||||
text = "I went for 40.3, and got home by 10.0."
|
||||
nlp = English()
|
||||
doc = nlp(text)
|
||||
|
||||
assert len(doc) == 11
|
||||
|
||||
assert doc[0].text == "I"
|
||||
assert doc[1].text == "went"
|
||||
assert doc[2].text == "for"
|
||||
assert doc[3].text == "40.3"
|
||||
assert doc[4].text == ","
|
||||
assert doc[5].text == "and"
|
||||
assert doc[6].text == "got"
|
||||
assert doc[7].text == "home"
|
||||
assert doc[8].text == "by"
|
||||
assert doc[9].text == "10.0"
|
||||
assert doc[10].text == "."
|
||||
21
spacy/tests/regression/test_issue2822.py
Normal file
21
spacy/tests/regression/test_issue2822.py
Normal file
|
|
@ -0,0 +1,21 @@
|
|||
# coding: utf8
|
||||
from __future__ import unicode_literals
|
||||
from spacy.lang.it import Italian
|
||||
|
||||
|
||||
def test_issue2822():
|
||||
""" Test that the abbreviation of poco is kept as one word """
|
||||
nlp = Italian()
|
||||
text = "Vuoi un po' di zucchero?"
|
||||
|
||||
doc = nlp(text)
|
||||
|
||||
assert len(doc) == 6
|
||||
|
||||
assert doc[0].text == "Vuoi"
|
||||
assert doc[1].text == "un"
|
||||
assert doc[2].text == "po'"
|
||||
assert doc[2].lemma_ == "poco"
|
||||
assert doc[3].text == "di"
|
||||
assert doc[4].text == "zucchero"
|
||||
assert doc[5].text == "?"
|
||||
21
spacy/tests/regression/test_issue2926.py
Normal file
21
spacy/tests/regression/test_issue2926.py
Normal file
|
|
@ -0,0 +1,21 @@
|
|||
# coding: utf8
|
||||
from __future__ import unicode_literals
|
||||
from spacy.lang.fr import French
|
||||
|
||||
|
||||
def test_issue2926():
|
||||
""" Test that the tokenizer correctly splits tokens separated by a slash (/) ending in a digit """
|
||||
nlp = French()
|
||||
text = "Learn html5/css3/javascript/jquery"
|
||||
doc = nlp(text)
|
||||
|
||||
assert len(doc) == 8
|
||||
|
||||
assert doc[0].text == "Learn"
|
||||
assert doc[1].text == "html5"
|
||||
assert doc[2].text == "/"
|
||||
assert doc[3].text == "css3"
|
||||
assert doc[4].text == "/"
|
||||
assert doc[5].text == "javascript"
|
||||
assert doc[6].text == "/"
|
||||
assert doc[7].text == "jquery"
|
||||
11
spacy/tests/regression/test_issue3002.py
Normal file
11
spacy/tests/regression/test_issue3002.py
Normal file
|
|
@ -0,0 +1,11 @@
|
|||
# coding: utf8
|
||||
from __future__ import unicode_literals
|
||||
|
||||
from spacy.lang.de import German
|
||||
|
||||
|
||||
def test_issue3002():
|
||||
"""Test that the tokenizer doesn't hang on a long list of dots"""
|
||||
nlp = German()
|
||||
doc = nlp('880.794.982.218.444.893.023.439.794.626.120.190.780.624.990.275.671 ist eine lange Zahl')
|
||||
assert len(doc) == 5
|
||||
|
|
@ -8,7 +8,6 @@ from spacy import displacy
|
|||
from ..util import get_doc
|
||||
|
||||
|
||||
@pytest.mark.xfail
|
||||
def test_issue3288(en_vocab):
|
||||
"""Test that retokenization works correctly via displaCy when punctuation
|
||||
is merged onto the preceeding token and tensor is resized."""
|
||||
|
|
|
|||
|
|
@ -5,7 +5,6 @@ import pytest
|
|||
from spacy.lang.en import English
|
||||
|
||||
|
||||
@pytest.mark.xfail
|
||||
def test_issue3289():
|
||||
"""Test that Language.to_bytes handles serializing a pipeline component
|
||||
with an uninitialized model."""
|
||||
|
|
|
|||
|
|
@ -9,104 +9,104 @@ import pytest
|
|||
|
||||
NAUGHTY_STRINGS = [
|
||||
# ASCII punctuation
|
||||
",./;'[]\-=",
|
||||
'<>?:"{}|_+',
|
||||
'!@#$%^&*()`~"',
|
||||
r",./;'[]\-=",
|
||||
r'<>?:"{}|_+',
|
||||
r'!@#$%^&*()`~"',
|
||||
# Unicode additional control characters, byte order marks
|
||||
"",
|
||||
"",
|
||||
r"",
|
||||
r"",
|
||||
# Unicode Symbols
|
||||
"Ω≈ç√∫˜µ≤≥÷",
|
||||
"åß∂ƒ©˙∆˚¬…æ",
|
||||
r"Ω≈ç√∫˜µ≤≥÷",
|
||||
r"åß∂ƒ©˙∆˚¬…æ",
|
||||
"œ∑´®†¥¨ˆøπ“‘",
|
||||
"¡™£¢∞§¶•ªº–≠",
|
||||
"¸˛Ç◊ı˜Â¯˘¿",
|
||||
"ÅÍÎÏ˝ÓÔÒÚÆ☃",
|
||||
"Œ„´‰ˇÁ¨ˆØ∏”’",
|
||||
"`⁄€‹›fifl‡°·‚—±",
|
||||
"⅛⅜⅝⅞",
|
||||
"ЁЂЃЄЅІЇЈЉЊЋЌЍЎЏАБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯабвгдежзийклмнопрстуфхцчшщъыьэюя",
|
||||
"٠١٢٣٤٥٦٧٨٩",
|
||||
r"¡™£¢∞§¶•ªº–≠",
|
||||
r"¸˛Ç◊ı˜Â¯˘¿",
|
||||
r"ÅÍÎÏ˝ÓÔÒÚÆ☃",
|
||||
r"Œ„´‰ˇÁ¨ˆØ∏”’",
|
||||
r"`⁄€‹›fifl‡°·‚—±",
|
||||
r"⅛⅜⅝⅞",
|
||||
r"ЁЂЃЄЅІЇЈЉЊЋЌЍЎЏАБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯабвгдежзийклмнопрстуфхцчшщъыьэюя",
|
||||
r"٠١٢٣٤٥٦٧٨٩",
|
||||
# Unicode Subscript/Superscript/Accents
|
||||
"⁰⁴⁵",
|
||||
"₀₁₂",
|
||||
"⁰⁴⁵₀₁₂",
|
||||
"ด้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็ ด้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็ ด้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็",
|
||||
r"⁰⁴⁵",
|
||||
r"₀₁₂",
|
||||
r"⁰⁴⁵₀₁₂",
|
||||
r"ด้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็ ด้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็ ด้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็",
|
||||
# Two-Byte Characters
|
||||
"田中さんにあげて下さい",
|
||||
"パーティーへ行かないか",
|
||||
"和製漢語",
|
||||
"部落格",
|
||||
"사회과학원 어학연구소",
|
||||
"찦차를 타고 온 펲시맨과 쑛다리 똠방각하",
|
||||
"社會科學院語學研究所",
|
||||
"울란바토르",
|
||||
"𠜎𠜱𠝹𠱓𠱸𠲖𠳏",
|
||||
r"田中さんにあげて下さい",
|
||||
r"パーティーへ行かないか",
|
||||
r"和製漢語",
|
||||
r"部落格",
|
||||
r"사회과학원 어학연구소",
|
||||
r"찦차를 타고 온 펲시맨과 쑛다리 똠방각하",
|
||||
r"社會科學院語學研究所",
|
||||
r"울란바토르",
|
||||
r"𠜎𠜱𠝹𠱓𠱸𠲖𠳏",
|
||||
# Japanese Emoticons
|
||||
"ヽ༼ຈل͜ຈ༽ﾉ ヽ༼ຈل͜ຈ༽ﾉ",
|
||||
"(｡◕ ∀ ◕｡)",
|
||||
"｀ｨ(´∀｀∩",
|
||||
"__ﾛ(,_,*)",
|
||||
"・(￣∀￣)・:*:",
|
||||
"ﾟ･✿ヾ╲(｡◕‿◕｡)╱✿･ﾟ",
|
||||
",。・:*:・゜’( ☻ ω ☻ )。・:*:・゜’",
|
||||
"(╯°□°）╯︵ ┻━┻)" "(ﾉಥ益ಥ）ﾉ ┻━┻",
|
||||
"┬─┬ノ( º _ ºノ)",
|
||||
"( ͡° ͜ʖ ͡°)",
|
||||
r"ヽ༼ຈل͜ຈ༽ﾉ ヽ༼ຈل͜ຈ༽ﾉ",
|
||||
r"(｡◕ ∀ ◕｡)",
|
||||
r"｀ｨ(´∀｀∩",
|
||||
r"__ﾛ(,_,*)",
|
||||
r"・(￣∀￣)・:*:",
|
||||
r"ﾟ･✿ヾ╲(｡◕‿◕｡)╱✿･ﾟ",
|
||||
r",。・:*:・゜’( ☻ ω ☻ )。・:*:・゜’",
|
||||
r"(╯°□°）╯︵ ┻━┻)" "(ﾉಥ益ಥ）ﾉ ┻━┻",
|
||||
r"┬─┬ノ( º _ ºノ)",
|
||||
r"( ͡° ͜ʖ ͡°)",
|
||||
# Emoji
|
||||
"😍",
|
||||
"👩🏽",
|
||||
"👾 🙇 💁 🙅 🙆 🙋 🙎 🙍",
|
||||
"🐵 🙈 🙉 🙊",
|
||||
"❤️ 💔 💌 💕 💞 💓 💗 💖 💘 💝 💟 💜 💛 💚 💙",
|
||||
"✋🏿 💪🏿 👐🏿 🙌🏿 👏🏿 🙏🏿",
|
||||
"🚾 🆒 🆓 🆕 🆖 🆗 🆙 🏧",
|
||||
"0️⃣ 1️⃣ 2️⃣ 3️⃣ 4️⃣ 5️⃣ 6️⃣ 7️⃣ 8️⃣ 9️⃣ 🔟",
|
||||
r"😍",
|
||||
r"👩🏽",
|
||||
r"👾 🙇 💁 🙅 🙆 🙋 🙎 🙍",
|
||||
r"🐵 🙈 🙉 🙊",
|
||||
r"❤️ 💔 💌 💕 💞 💓 💗 💖 💘 💝 💟 💜 💛 💚 💙",
|
||||
r"✋🏿 💪🏿 👐🏿 🙌🏿 👏🏿 🙏🏿",
|
||||
r"🚾 🆒 🆓 🆕 🆖 🆗 🆙 🏧",
|
||||
r"0️⃣ 1️⃣ 2️⃣ 3️⃣ 4️⃣ 5️⃣ 6️⃣ 7️⃣ 8️⃣ 9️⃣ 🔟",
|
||||
# Regional Indicator Symbols
|
||||
"🇺🇸🇷🇺🇸 🇦🇫🇦🇲🇸",
|
||||
"🇺🇸🇷🇺🇸🇦🇫🇦🇲",
|
||||
"🇺🇸🇷🇺🇸🇦",
|
||||
r"🇺🇸🇷🇺🇸 🇦🇫🇦🇲🇸",
|
||||
r"🇺🇸🇷🇺🇸🇦🇫🇦🇲",
|
||||
r"🇺🇸🇷🇺🇸🇦",
|
||||
# Unicode Numbers
|
||||
"１２３",
|
||||
"١٢٣",
|
||||
r"１２３",
|
||||
r"١٢٣",
|
||||
# Right-To-Left Strings
|
||||
"ثم نفس سقطت وبالتحديد،, جزيرتي باستخدام أن دنو. إذ هنا؟ الستار وتنصيب كان. أهّل ايطاليا، بريطانيا-فرنسا قد أخذ. سليمان، إتفاقية بين ما, يذكر الحدود أي بعد, معاملة بولندا، الإطلاق عل إيو.",
|
||||
"إيو.",
|
||||
"בְּרֵאשִׁית, בָּרָא אֱלֹהִים, אֵת הַשָּׁמַיִם, וְאֵת הָאָרֶץ",
|
||||
"הָיְתָהtestالصفحات التّحول",
|
||||
"﷽",
|
||||
"ﷺ",
|
||||
"مُنَاقَشَةُ سُبُلِ اِسْتِخْدَامِ اللُّغَةِ فِي النُّظُمِ الْقَائِمَةِ وَفِيم يَخُصَّ التَّطْبِيقَاتُ الْحاسُوبِيَّةُ،",
|
||||
r"ثم نفس سقطت وبالتحديد،, جزيرتي باستخدام أن دنو. إذ هنا؟ الستار وتنصيب كان. أهّل ايطاليا، بريطانيا-فرنسا قد أخذ. سليمان، إتفاقية بين ما, يذكر الحدود أي بعد, معاملة بولندا، الإطلاق عل إيو.",
|
||||
r"إيو.",
|
||||
r"בְּרֵאשִׁית, בָּרָא אֱלֹהִים, אֵת הַשָּׁמַיִם, וְאֵת הָאָרֶץ",
|
||||
r"הָיְתָהtestالصفحات التّحول",
|
||||
r"﷽",
|
||||
r"ﷺ",
|
||||
r"مُنَاقَشَةُ سُبُلِ اِسْتِخْدَامِ اللُّغَةِ فِي النُّظُمِ الْقَائِمَةِ وَفِيم يَخُصَّ التَّطْبِيقَاتُ الْحاسُوبِيَّةُ،",
|
||||
# Trick Unicode
|
||||
"test",
|
||||
"test",
|
||||
"
test
",
|
||||
"testtest",
|
||||
"test",
|
||||
r"test",
|
||||
r"test",
|
||||
r"
test
",
|
||||
r"testtest",
|
||||
r"test",
|
||||
# Zalgo Text
|
||||
"Ṱ̺̺̕o͞ ̷i̲̬͇̪͙n̝̗͕v̟̜̘̦͟o̶̙̰̠kè͚̮̺̪̹̱̤ ̖t̝͕̳̣̻̪͞h̼͓̲̦̳̘̲e͇̣̰̦̬͎ ̢̼̻̱̘h͚͎͙̜̣̲ͅi̦̲̣̰̤v̻͍e̺̭̳̪̰-m̢iͅn̖̺̞̲̯̰d̵̼̟͙̩̼̘̳ ̞̥̱̳̭r̛̗̘e͙p͠r̼̞̻̭̗e̺̠̣͟s̘͇̳͍̝͉e͉̥̯̞̲͚̬͜ǹ̬͎͎̟̖͇̤t͍̬̤͓̼̭͘ͅi̪̱n͠g̴͉ ͏͉ͅc̬̟h͡a̫̻̯͘o̫̟̖͍̙̝͉s̗̦̲.̨̹͈̣",
|
||||
"̡͓̞ͅI̗̘̦͝n͇͇͙v̮̫ok̲̫̙͈i̖͙̭̹̠̞n̡̻̮̣̺g̲͈͙̭͙̬͎ ̰t͔̦h̞̲e̢̤ ͍̬̲͖f̴̘͕̣è͖ẹ̥̩l͖͔͚i͓͚̦͠n͖͍̗͓̳̮g͍ ̨o͚̪͡f̘̣̬ ̖̘͖̟͙̮c҉͔̫͖͓͇͖ͅh̵̤̣͚͔á̗̼͕ͅo̼̣̥s̱͈̺̖̦̻͢.̛̖̞̠̫̰",
|
||||
"̗̺͖̹̯͓Ṯ̤͍̥͇͈h̲́e͏͓̼̗̙̼̣͔ ͇̜̱̠͓͍ͅN͕͠e̗̱z̘̝̜̺͙p̤̺̹͍̯͚e̠̻̠͜r̨̤͍̺̖͔̖̖d̠̟̭̬̝͟i̦͖̩͓͔̤a̠̗̬͉̙n͚͜ ̻̞̰͚ͅh̵͉i̳̞v̢͇ḙ͎͟-҉̭̩̼͔m̤̭̫i͕͇̝̦n̗͙ḍ̟ ̯̲͕͞ǫ̟̯̰̲͙̻̝f ̪̰̰̗̖̭̘͘c̦͍̲̞͍̩̙ḥ͚a̮͎̟̙͜ơ̩̹͎s̤.̝̝ ҉Z̡̖̜͖̰̣͉̜a͖̰͙̬͡l̲̫̳͍̩g̡̟̼̱͚̞̬ͅo̗͜.̟",
|
||||
"̦H̬̤̗̤͝e͜ ̜̥̝̻͍̟́w̕h̖̯͓o̝͙̖͎̱̮ ҉̺̙̞̟͈W̷̼̭a̺̪͍į͈͕̭͙̯̜t̶̼̮s̘͙͖̕ ̠̫̠B̻͍͙͉̳ͅe̵h̵̬͇̫͙i̹͓̳̳̮͎̫̕n͟d̴̪̜̖ ̰͉̩͇͙̲͞ͅT͖̼͓̪͢h͏͓̮̻e̬̝̟ͅ ̤̹̝W͙̞̝͔͇͝ͅa͏͓͔̹̼̣l̴͔̰̤̟͔ḽ̫.͕",
|
||||
"Z̮̞̠͙͔ͅḀ̗̞͈̻̗Ḷ͙͎̯̹̞͓G̻O̭̗̮",
|
||||
r"Ṱ̺̺̕o͞ ̷i̲̬͇̪͙n̝̗͕v̟̜̘̦͟o̶̙̰̠kè͚̮̺̪̹̱̤ ̖t̝͕̳̣̻̪͞h̼͓̲̦̳̘̲e͇̣̰̦̬͎ ̢̼̻̱̘h͚͎͙̜̣̲ͅi̦̲̣̰̤v̻͍e̺̭̳̪̰-m̢iͅn̖̺̞̲̯̰d̵̼̟͙̩̼̘̳ ̞̥̱̳̭r̛̗̘e͙p͠r̼̞̻̭̗e̺̠̣͟s̘͇̳͍̝͉e͉̥̯̞̲͚̬͜ǹ̬͎͎̟̖͇̤t͍̬̤͓̼̭͘ͅi̪̱n͠g̴͉ ͏͉ͅc̬̟h͡a̫̻̯͘o̫̟̖͍̙̝͉s̗̦̲.̨̹͈̣",
|
||||
r"̡͓̞ͅI̗̘̦͝n͇͇͙v̮̫ok̲̫̙͈i̖͙̭̹̠̞n̡̻̮̣̺g̲͈͙̭͙̬͎ ̰t͔̦h̞̲e̢̤ ͍̬̲͖f̴̘͕̣è͖ẹ̥̩l͖͔͚i͓͚̦͠n͖͍̗͓̳̮g͍ ̨o͚̪͡f̘̣̬ ̖̘͖̟͙̮c҉͔̫͖͓͇͖ͅh̵̤̣͚͔á̗̼͕ͅo̼̣̥s̱͈̺̖̦̻͢.̛̖̞̠̫̰",
|
||||
r"̗̺͖̹̯͓Ṯ̤͍̥͇͈h̲́e͏͓̼̗̙̼̣͔ ͇̜̱̠͓͍ͅN͕͠e̗̱z̘̝̜̺͙p̤̺̹͍̯͚e̠̻̠͜r̨̤͍̺̖͔̖̖d̠̟̭̬̝͟i̦͖̩͓͔̤a̠̗̬͉̙n͚͜ ̻̞̰͚ͅh̵͉i̳̞v̢͇ḙ͎͟-҉̭̩̼͔m̤̭̫i͕͇̝̦n̗͙ḍ̟ ̯̲͕͞ǫ̟̯̰̲͙̻̝f ̪̰̰̗̖̭̘͘c̦͍̲̞͍̩̙ḥ͚a̮͎̟̙͜ơ̩̹͎s̤.̝̝ ҉Z̡̖̜͖̰̣͉̜a͖̰͙̬͡l̲̫̳͍̩g̡̟̼̱͚̞̬ͅo̗͜.̟",
|
||||
r"̦H̬̤̗̤͝e͜ ̜̥̝̻͍̟́w̕h̖̯͓o̝͙̖͎̱̮ ҉̺̙̞̟͈W̷̼̭a̺̪͍į͈͕̭͙̯̜t̶̼̮s̘͙͖̕ ̠̫̠B̻͍͙͉̳ͅe̵h̵̬͇̫͙i̹͓̳̳̮͎̫̕n͟d̴̪̜̖ ̰͉̩͇͙̲͞ͅT͖̼͓̪͢h͏͓̮̻e̬̝̟ͅ ̤̹̝W͙̞̝͔͇͝ͅa͏͓͔̹̼̣l̴͔̰̤̟͔ḽ̫.͕",
|
||||
r"Z̮̞̠͙͔ͅḀ̗̞͈̻̗Ḷ͙͎̯̹̞͓G̻O̭̗̮",
|
||||
# Unicode Upsidedown
|
||||
"˙ɐnbᴉlɐ ɐuƃɐɯ ǝɹolop ʇǝ ǝɹoqɐl ʇn ʇunpᴉpᴉɔuᴉ ɹodɯǝʇ poɯsnᴉǝ op pǝs 'ʇᴉlǝ ƃuᴉɔsᴉdᴉpɐ ɹnʇǝʇɔǝsuoɔ 'ʇǝɯɐ ʇᴉs ɹolop ɯnsdᴉ ɯǝɹo˥",
|
||||
"00˙Ɩ$-",
|
||||
r"˙ɐnbᴉlɐ ɐuƃɐɯ ǝɹolop ʇǝ ǝɹoqɐl ʇn ʇunpᴉpᴉɔuᴉ ɹodɯǝʇ poɯsnᴉǝ op pǝs 'ʇᴉlǝ ƃuᴉɔsᴉdᴉpɐ ɹnʇǝʇɔǝsuoɔ 'ʇǝɯɐ ʇᴉs ɹolop ɯnsdᴉ ɯǝɹo˥",
|
||||
r"00˙Ɩ$-",
|
||||
# Unicode font
|
||||
"Ｔｈｅ ｑｕｉｃｋ ｂｒｏｗｎ ｆｏｘ ｊｕｍｐｓ ｏｖｅｒ ｔｈｅ ｌａｚｙ ｄｏｇ",
|
||||
"𝐓𝐡𝐞 𝐪𝐮𝐢𝐜𝐤 𝐛𝐫𝐨𝐰𝐧 𝐟𝐨𝐱 𝐣𝐮𝐦𝐩𝐬 𝐨𝐯𝐞𝐫 𝐭𝐡𝐞 𝐥𝐚𝐳𝐲 𝐝𝐨𝐠",
|
||||
"𝕿𝖍𝖊 𝖖𝖚𝖎𝖈𝖐 𝖇𝖗𝖔𝖜𝖓 𝖋𝖔𝖝 𝖏𝖚𝖒𝖕𝖘 𝖔𝖛𝖊𝖗 𝖙𝖍𝖊 𝖑𝖆𝖟𝖞 𝖉𝖔𝖌",
|
||||
"𝑻𝒉𝒆 𝒒𝒖𝒊𝒄𝒌 𝒃𝒓𝒐𝒘𝒏 𝒇𝒐𝒙 𝒋𝒖𝒎𝒑𝒔 𝒐𝒗𝒆𝒓 𝒕𝒉𝒆 𝒍𝒂𝒛𝒚 𝒅𝒐𝒈",
|
||||
"𝓣𝓱𝓮 𝓺𝓾𝓲𝓬𝓴 𝓫𝓻𝓸𝔀𝓷 𝓯𝓸𝔁 𝓳𝓾𝓶𝓹𝓼 𝓸𝓿𝓮𝓻 𝓽𝓱𝓮 𝓵𝓪𝔃𝔂 𝓭𝓸𝓰",
|
||||
"𝕋𝕙𝕖 𝕢𝕦𝕚𝕔𝕜 𝕓𝕣𝕠𝕨𝕟 𝕗𝕠𝕩 𝕛𝕦𝕞𝕡𝕤 𝕠𝕧𝕖𝕣 𝕥𝕙𝕖 𝕝𝕒𝕫𝕪 𝕕𝕠𝕘",
|
||||
"𝚃𝚑𝚎 𝚚𝚞𝚒𝚌𝚔 𝚋𝚛𝚘𝚠𝚗 𝚏𝚘𝚡 𝚓𝚞𝚖𝚙𝚜 𝚘𝚟𝚎𝚛 𝚝𝚑𝚎 𝚕𝚊𝚣𝚢 𝚍𝚘𝚐",
|
||||
"⒯⒣⒠ ⒬⒰⒤⒞⒦ ⒝⒭⒪⒲⒩ ⒡⒪⒳ ⒥⒰⒨⒫⒮ ⒪⒱⒠⒭ ⒯⒣⒠ ⒧⒜⒵⒴ ⒟⒪⒢",
|
||||
r"Ｔｈｅ ｑｕｉｃｋ ｂｒｏｗｎ ｆｏｘ ｊｕｍｐｓ ｏｖｅｒ ｔｈｅ ｌａｚｙ ｄｏｇ",
|
||||
r"𝐓𝐡𝐞 𝐪𝐮𝐢𝐜𝐤 𝐛𝐫𝐨𝐰𝐧 𝐟𝐨𝐱 𝐣𝐮𝐦𝐩𝐬 𝐨𝐯𝐞𝐫 𝐭𝐡𝐞 𝐥𝐚𝐳𝐲 𝐝𝐨𝐠",
|
||||
r"𝕿𝖍𝖊 𝖖𝖚𝖎𝖈𝖐 𝖇𝖗𝖔𝖜𝖓 𝖋𝖔𝖝 𝖏𝖚𝖒𝖕𝖘 𝖔𝖛𝖊𝖗 𝖙𝖍𝖊 𝖑𝖆𝖟𝖞 𝖉𝖔𝖌",
|
||||
r"𝑻𝒉𝒆 𝒒𝒖𝒊𝒄𝒌 𝒃𝒓𝒐𝒘𝒏 𝒇𝒐𝒙 𝒋𝒖𝒎𝒑𝒔 𝒐𝒗𝒆𝒓 𝒕𝒉𝒆 𝒍𝒂𝒛𝒚 𝒅𝒐𝒈",
|
||||
r"𝓣𝓱𝓮 𝓺𝓾𝓲𝓬𝓴 𝓫𝓻𝓸𝔀𝓷 𝓯𝓸𝔁 𝓳𝓾𝓶𝓹𝓼 𝓸𝓿𝓮𝓻 𝓽𝓱𝓮 𝓵𝓪𝔃𝔂 𝓭𝓸𝓰",
|
||||
r"𝕋𝕙𝕖 𝕢𝕦𝕚𝕔𝕜 𝕓𝕣𝕠𝕨𝕟 𝕗𝕠𝕩 𝕛𝕦𝕞𝕡𝕤 𝕠𝕧𝕖𝕣 𝕥𝕙𝕖 𝕝𝕒𝕫𝕪 𝕕𝕠𝕘",
|
||||
r"𝚃𝚑𝚎 𝚚𝚞𝚒𝚌𝚔 𝚋𝚛𝚘𝚠𝚗 𝚏𝚘𝚡 𝚓𝚞𝚖𝚙𝚜 𝚘𝚟𝚎𝚛 𝚝𝚑𝚎 𝚕𝚊𝚣𝚢 𝚍𝚘𝚐",
|
||||
r"⒯⒣⒠ ⒬⒰⒤⒞⒦ ⒝⒭⒪⒲⒩ ⒡⒪⒳ ⒥⒰⒨⒫⒮ ⒪⒱⒠⒭ ⒯⒣⒠ ⒧⒜⒵⒴ ⒟⒪⒢",
|
||||
# File paths
|
||||
"../../../../../../../../../../../etc/passwd%00",
|
||||
"../../../../../../../../../../../etc/hosts",
|
||||
r"../../../../../../../../../../../etc/passwd%00",
|
||||
r"../../../../../../../../../../../etc/hosts",
|
||||
# iOS Vulnerabilities
|
||||
"Powerلُلُصّبُلُلصّبُررً ॣ ॣh ॣ ॣ冗",
|
||||
"🏳0🌈️",
|
||||
r"Powerلُلُصّبُلُلصّبُررً ॣ ॣh ॣ ॣ冗",
|
||||
r"🏳0🌈️",
|
||||
]
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -407,7 +407,7 @@ cdef class Tokenizer:
|
|||
if data.get('infix_finditer'):
|
||||
self.infix_finditer = re.compile(data['infix_finditer']).finditer
|
||||
if data.get('token_match'):
|
||||
self.token_match = re.compile(data['token_match']).search
|
||||
self.token_match = re.compile(data['token_match']).match
|
||||
for string, substrings in data.get('rules', {}).items():
|
||||
self.add_special_case(string, substrings)
|
||||
return self
|
||||
|
|
|
|||
|
|
@ -222,7 +222,7 @@ def _bulk_merge(Doc doc, merges):
|
|||
# whether the row is to be deleted, then use numpy.delete
|
||||
if doc.tensor is not None and doc.tensor.size != 0:
|
||||
doc.tensor = _resize_tensor(doc.tensor,
|
||||
[(m[1][0].start, m[1][0].end) for m in merges])
|
||||
[(m[0].start, m[0].end) for m in merges])
|
||||
# Memorize span roots and sets dependencies of the newly merged
|
||||
# tokens to the dependencies of their roots.
|
||||
span_roots = []
|
||||
|
|
|
|||
|
|
@ -102,11 +102,12 @@ language and training a language model.
|
|||
|
||||
In order for the tokenizer to split suffixes, prefixes and infixes, spaCy needs
|
||||
to know the language's character set. If the language you're adding uses
|
||||
non-latin characters, you might need to add the required character classes to
|
||||
non-latin characters, you might need to define the required character classes in
|
||||
the global
|
||||
[`char_classes.py`](https://github.com/explosion/spaCy/tree/master/spacy/lang/char_classes.py).
|
||||
spaCy uses the [`regex` library](https://pypi.python.org/pypi/regex/) to keep
|
||||
this simple and readable. If the language requires very specific punctuation
|
||||
For efficiency, spaCy uses hard-coded unicode ranges to define character classes,
|
||||
the definitions of which can be found on [Wikipedia](https://en.wikipedia.org/wiki/Unicode_block).
|
||||
If the language requires very specific punctuation
|
||||
rules, you should consider overwriting the default regular expressions with your
|
||||
own in the language's `Defaults`.
|
||||
|
||||
|
|
|
|||
|
|
@ -215,6 +215,22 @@ if all of your models are up to date, you can run the
|
|||
means that the `Matcher` in v2.1.x may produce different results compared to
|
||||
the `Matcher` in v2.0.x.
|
||||
|
||||
- The deprecated [`Doc.merge`](/api/doc#merge) and
|
||||
[`Span.merge`](/api/span#merge) methods still work, but you may notice that
|
||||
they now run slower when merging many objects in a row. That's because the
|
||||
merging engine was rewritten to be more reliable and to support more efficient
|
||||
merging **in bulk**. To take advantage of this, you should rewrite your logic
|
||||
to use the [`Doc.retokenize`](/api/doc#retokenize) context manager and perform
|
||||
as many merges as possible together in the `with` block.
|
||||
|
||||
```diff
|
||||
- doc[1:5].merge()
|
||||
- doc[6:8].merge()
|
||||
+ with doc.retokenize() as retokenizer:
|
||||
+ retokenizer.merge(doc[1:5])
|
||||
+ retokenizer.merge(doc[6:8])
|
||||
```
|
||||
|
||||
- For better compatibility with the Universal Dependencies data, the lemmatizer
|
||||
now preserves capitalization, e.g. for proper nouns. See
|
||||
[this issue](https://github.com/explosion/spaCy/issues/3256) for details.
|
||||
|
|
@ -227,6 +243,11 @@ if all of your models are up to date, you can run the
|
|||
+ sentence_splitter = nlp.create_pipe("sentencizer")
|
||||
```
|
||||
|
||||
- The keyword argument `n_threads` on the `.pipe` methods is now deprecated, as
|
||||
the v2.x models cannot release the global interpreter lock. (Future versions
|
||||
may introduce a `n_process` argument for parallel inference via
|
||||
multiprocessing.)
|
||||
|
||||
- The `Doc.print_tree` method is now deprecated. If you need a custom nested
|
||||
JSON representation of a `Doc` object, you might want to write your own helper
|
||||
function. For a simple and consistent JSON representation of the `Doc` object
|
||||
|
|
|
|||
|
|
@ -1,4 +1,7 @@
|
|||
redirects = [
|
||||
# Netlify
|
||||
# TODO: uncomment once the site is switched over
|
||||
# {from = "https://spacy.netlify.com/*", to="https://spacy.io/:splat" },
|
||||
# Old demos
|
||||
{from = "/demos/*", to = "https://explosion.ai/demos/:splat"},
|
||||
# Old blog
|
||||
|
|
|
|||
|
|
@ -71,11 +71,11 @@ const SEO = ({ description, lang, title, section, sectionTitle, bodyClass }) =>
|
|||
},
|
||||
{
|
||||
name: 'twitter:creator',
|
||||
content: `@${data.site.siteMetadata.social.twitter}`,
|
||||
content: `@${siteMetadata.social.twitter}`,
|
||||
},
|
||||
{
|
||||
name: 'twitter:site',
|
||||
content: `@${data.site.siteMetadata.social.twitter}`,
|
||||
content: `@${siteMetadata.social.twitter}`,
|
||||
},
|
||||
{
|
||||
name: 'twitter:title',
|
||||
|
|
@ -126,8 +126,6 @@ const query = graphql`
|
|||
title
|
||||
description
|
||||
slogan
|
||||
siteUrl
|
||||
email
|
||||
social {
|
||||
twitter
|
||||
}
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user