explosion/spaCy
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Fix issue #535: Pipeline elements added even when data not installed.

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This commit is contained in:
Matthew Honnibal 2016-10-19 19:55:19 +02:00
parent ca89fd0919
commit d4aaf2752c
1 changed files with 12 additions and 4 deletions
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16
spacy/language.py
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@ -70,8 +70,10 @@ class BaseDefaults(object):
def create_tagger(cls, nlp=None): def create_tagger(cls, nlp=None):
if nlp is None: if nlp is None:
return Tagger(cls.create_vocab(), features=cls.tagger_features) return Tagger(cls.create_vocab(), features=cls.tagger_features)
elif nlp.path is None or not (nlp.path / 'pos').exists(): elif nlp.path is None:
return Tagger(nlp.vocab, features=cls.tagger_features) return Tagger(nlp.vocab, features=cls.tagger_features)
elif not (nlp.path / 'pos').exists():
return None
else: else:
return Tagger.load(nlp.path / 'pos', nlp.vocab) return Tagger.load(nlp.path / 'pos', nlp.vocab)
@ -79,8 +81,10 @@ class BaseDefaults(object):
def create_parser(cls, nlp=None): def create_parser(cls, nlp=None):
if nlp is None: if nlp is None:
return DependencyParser(cls.create_vocab(), features=cls.parser_features) return DependencyParser(cls.create_vocab(), features=cls.parser_features)
elif nlp.path is None or not (nlp.path / 'deps').exists(): elif nlp.path is None:
return DependencyParser(nlp.vocab, features=cls.parser_features) return DependencyParser(nlp.vocab, features=cls.parser_features)
elif not (nlp.path / 'deps').exists():
return None
else: else:
return DependencyParser.load(nlp.path / 'deps', nlp.vocab) return DependencyParser.load(nlp.path / 'deps', nlp.vocab)
@ -88,8 +92,10 @@ class BaseDefaults(object):
def create_entity(cls, nlp=None): def create_entity(cls, nlp=None):
if nlp is None: if nlp is None:
return EntityRecognizer(cls.create_vocab(), features=cls.entity_features) return EntityRecognizer(cls.create_vocab(), features=cls.entity_features)
elif nlp.path is None or not (nlp.path / 'ner').exists(): elif nlp.path is None:
return EntityRecognizer(nlp.vocab, features=cls.entity_features) return EntityRecognizer(nlp.vocab, features=cls.entity_features)
elif not (nlp.path / 'ner').exists():
return None
else: else:
return EntityRecognizer.load(nlp.path / 'ner', nlp.vocab) return EntityRecognizer.load(nlp.path / 'ner', nlp.vocab)
@ -97,8 +103,10 @@ class BaseDefaults(object):
def create_matcher(cls, nlp=None): def create_matcher(cls, nlp=None):
if nlp is None: if nlp is None:
return Matcher(cls.create_vocab()) return Matcher(cls.create_vocab())
elif nlp.path is None or not (nlp.path / 'vocab').exists(): elif nlp.path is None:
return Matcher(nlp.vocab) return Matcher(nlp.vocab)
elif not (nlp.path / 'vocab').exists():
return None
else: else:
return Matcher.load(nlp.path / 'vocab', nlp.vocab) return Matcher.load(nlp.path / 'vocab', nlp.vocab)