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https://github.com/explosion/spaCy.git
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Merge branch 'master' into develop
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commit
bf2cc370fe
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@ -4,6 +4,7 @@ This is a list of everyone who has made significant contributions to spaCy, in a
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* Adam Bittlingmayer, [@bittlingmayer](https://github.com/bittlingmayer)
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* Andreas Grivas, [@andreasgrv](https://github.com/andreasgrv)
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* Andrew Poliakov, [@pavlin99th](https://github.com/pavlin99th)
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* Aniruddha Adhikary [@aniruddha-adhikary](https://github.com/aniruddha-adhikary)
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* Bhargav Srinivasa, [@bhargavvader](https://github.com/bhargavvader)
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* Chris DuBois, [@chrisdubois](https://github.com/chrisdubois)
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@ -11,12 +12,16 @@ This is a list of everyone who has made significant contributions to spaCy, in a
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* Dafne van Kuppevelt, [@dafnevk](https://github.com/dafnevk)
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* Daniel Rapp, [@rappdw](https://github.com/rappdw)
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* Dmytro Sadovnychyi, [@sadovnychyi](https://github.com/sadovnychyi)
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* Eric Zhao, [@ericzhao28](https://github.com/ericzhao28)
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* Greg Baker, [@solresol](https://github.com/solresol)
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* György Orosz, [@oroszgy](https://github.com/oroszgy)
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* Henning Peters, [@henningpeters](https://github.com/henningpeters)
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* Iddo Berger, [@iddoberger](https://github.com/iddoberger)
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* Ines Montani, [@ines](https://github.com/ines)
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* J Nicolas Schrading, [@NSchrading](https://github.com/NSchrading)
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* Janneke van der Zwaan, [@jvdzwaan](https://github.com/jvdzwaan)
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* Jordan Suchow, [@suchow](https://github.com/suchow)
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* Juan Miguel Cejuela, [@juanmirocks](https://github.com/juanmirocks)
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* Kendrick Tan, [@kendricktan](https://github.com/kendricktan)
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* Kyle P. Johnson, [@kylepjohnson](https://github.com/kylepjohnson)
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* Liling Tan, [@alvations](https://github.com/alvations)
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@ -29,6 +34,7 @@ This is a list of everyone who has made significant contributions to spaCy, in a
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* Pokey Rule, [@pokey](https://github.com/pokey)
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* Raphaël Bournhonesque, [@raphael0202](https://github.com/raphael0202)
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* Rob van Nieuwpoort, [@RvanNieuwpoort](https://github.com/RvanNieuwpoort)
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* Roman Inflianskas, [@rominf](https://github.com/rominf)
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* Sam Bozek, [@sambozek](https://github.com/sambozek)
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* Sasho Savkov, [@savkov](https://github.com/savkov)
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* Shuvanon Razik, [@shuvanon](https://github.com/shuvanon)
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@ -5,8 +5,8 @@ spaCy is a library for advanced natural language processing in Python and
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Cython. spaCy is built on the very latest research, but it isn't researchware.
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It was designed from day one to be used in real products. spaCy currently supports
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English and German, as well as tokenization for Chinese, Spanish, Italian, French,
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Portuguese, Dutch, Swedish, Finnish, Hungarian and Bengali. It's commercial open-source
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software, released under the MIT license.
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Portuguese, Dutch, Swedish, Finnish, Hungarian, Bengali and Hebrew. It's commercial
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open-source software, released under the MIT license.
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💫 **Version 1.7 out now!** `Read the release notes here. <https://github.com/explosion/spaCy/releases/>`_
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@ -316,6 +316,7 @@ and ``--model`` are optional and enable additional tests:
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=========== ============== ===========
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Version Date Description
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=========== ============== ===========
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`v1.7.3`_ ``2017-03-26`` Alpha support for Hebrew, new CLI commands and bug fixes
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`v1.7.2`_ ``2017-03-20`` Small fixes to beam parser and model linking
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`v1.7.1`_ ``2017-03-19`` Fix data download for system installation
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`v1.7.0`_ ``2017-03-18`` New 50 MB model, CLI, better downloads and lots of bug fixes
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@ -344,6 +345,7 @@ Version Date Description
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`v0.93`_ ``2015-09-22`` Bug fixes to word vectors
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=========== ============== ===========
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.. _v1.7.3: https://github.com/explosion/spaCy/releases/tag/v1.7.3
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.. _v1.7.2: https://github.com/explosion/spaCy/releases/tag/v1.7.2
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.. _v1.7.1: https://github.com/explosion/spaCy/releases/tag/v1.7.1
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.. _v1.7.0: https://github.com/explosion/spaCy/releases/tag/v1.7.0
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@ -14,7 +14,7 @@ from spacy.cli import train as cli_train
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class CLI(object):
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"""Command-line interface for spaCy"""
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commands = ('download', 'link', 'info', 'package', 'train', 'train_config')
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commands = ('download', 'link', 'info', 'package', 'train')
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@plac.annotations(
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model=("model to download (shortcut or model name)", "positional", None, str),
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@ -3,7 +3,7 @@
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# https://github.com/pypa/warehouse/blob/master/warehouse/__about__.py
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__title__ = 'spacy'
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__version__ = '1.7.2'
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__version__ = '1.7.3'
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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__ = 'Matthew Honnibal'
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@ -93,7 +93,7 @@ def evaluate(Language, gold_tuples, output_path):
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def check_dirs(output_path, train_path, dev_path):
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if not output_path.exists():
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util.sys_exit(output_path.as_posix(), title="Output directory not found")
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if not train_path.exists() or not train_path.is_file():
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if not train_path.exists():
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util.sys_exit(train_path.as_posix(), title="Training data not found")
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if dev_path and not dev_path.exists():
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util.sys_exit(dev_path.as_posix(), title="Development data not found")
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@ -278,7 +278,8 @@ class Language(object):
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path = pathlib.Path(path)
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if path is True:
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path = util.get_data_path() / self.lang
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if not path.exists() and 'path' not in overrides:
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path = None
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self.meta = overrides.get('meta', {})
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self.path = path
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@ -52,7 +52,7 @@ from ._parse_features cimport fill_context
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from .stateclass cimport StateClass
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from ._state cimport StateC
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USE_FTRL = False
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USE_FTRL = True
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DEBUG = False
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def set_debug(val):
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global DEBUG
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@ -82,14 +82,19 @@ cdef class ParserModel(AveragedPerceptron):
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def update(self, Example eg, itn=0):
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'''Does regression on negative cost. Sort of cute?'''
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self.time += 1
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best = arg_max_if_gold(eg.c.scores, eg.c.costs, eg.c.nr_class)
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guess = eg.guess
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cdef int best = arg_max_if_gold(eg.c.scores, eg.c.costs, eg.c.nr_class)
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cdef int guess = eg.guess
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if guess == best or best == -1:
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return 0.0
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cdef FeatureC feat
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cdef int clas
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cdef weight_t gradient
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if USE_FTRL:
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for feat in eg.c.features[:eg.c.nr_feat]:
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self.update_weight_ftrl(feat.key, guess, feat.value * eg.c.costs[guess])
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self.update_weight_ftrl(feat.key, best, -feat.value * eg.c.costs[guess])
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for clas in range(eg.c.nr_class):
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if eg.c.is_valid[clas] and eg.c.scores[clas] >= eg.c.scores[best]:
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gradient = eg.c.scores[clas] + eg.c.costs[clas]
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self.update_weight_ftrl(feat.key, clas, feat.value * gradient)
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else:
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for feat in eg.c.features[:eg.c.nr_feat]:
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self.update_weight(feat.key, guess, feat.value * eg.c.costs[guess])
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