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Fix issue #535: Pipeline elements added even when data not installed.
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parent
ca89fd0919
commit
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@ -70,8 +70,10 @@ class BaseDefaults(object):
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def create_tagger(cls, nlp=None):
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def create_tagger(cls, nlp=None):
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if nlp is None:
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if nlp is None:
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return Tagger(cls.create_vocab(), features=cls.tagger_features)
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return Tagger(cls.create_vocab(), features=cls.tagger_features)
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elif nlp.path is None or not (nlp.path / 'pos').exists():
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elif nlp.path is None:
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return Tagger(nlp.vocab, features=cls.tagger_features)
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return Tagger(nlp.vocab, features=cls.tagger_features)
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elif not (nlp.path / 'pos').exists():
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return None
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else:
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else:
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return Tagger.load(nlp.path / 'pos', nlp.vocab)
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return Tagger.load(nlp.path / 'pos', nlp.vocab)
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@ -79,8 +81,10 @@ class BaseDefaults(object):
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def create_parser(cls, nlp=None):
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def create_parser(cls, nlp=None):
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if nlp is None:
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if nlp is None:
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return DependencyParser(cls.create_vocab(), features=cls.parser_features)
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return DependencyParser(cls.create_vocab(), features=cls.parser_features)
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elif nlp.path is None or not (nlp.path / 'deps').exists():
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elif nlp.path is None:
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return DependencyParser(nlp.vocab, features=cls.parser_features)
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return DependencyParser(nlp.vocab, features=cls.parser_features)
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elif not (nlp.path / 'deps').exists():
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return None
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else:
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else:
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return DependencyParser.load(nlp.path / 'deps', nlp.vocab)
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return DependencyParser.load(nlp.path / 'deps', nlp.vocab)
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@ -88,8 +92,10 @@ class BaseDefaults(object):
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def create_entity(cls, nlp=None):
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def create_entity(cls, nlp=None):
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if nlp is None:
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if nlp is None:
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return EntityRecognizer(cls.create_vocab(), features=cls.entity_features)
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return EntityRecognizer(cls.create_vocab(), features=cls.entity_features)
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elif nlp.path is None or not (nlp.path / 'ner').exists():
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elif nlp.path is None:
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return EntityRecognizer(nlp.vocab, features=cls.entity_features)
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return EntityRecognizer(nlp.vocab, features=cls.entity_features)
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elif not (nlp.path / 'ner').exists():
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return None
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else:
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else:
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return EntityRecognizer.load(nlp.path / 'ner', nlp.vocab)
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return EntityRecognizer.load(nlp.path / 'ner', nlp.vocab)
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@ -97,8 +103,10 @@ class BaseDefaults(object):
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def create_matcher(cls, nlp=None):
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def create_matcher(cls, nlp=None):
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if nlp is None:
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if nlp is None:
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return Matcher(cls.create_vocab())
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return Matcher(cls.create_vocab())
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elif nlp.path is None or not (nlp.path / 'vocab').exists():
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elif nlp.path is None:
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return Matcher(nlp.vocab)
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return Matcher(nlp.vocab)
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elif not (nlp.path / 'vocab').exists():
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return None
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else:
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else:
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return Matcher.load(nlp.path / 'vocab', nlp.vocab)
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return Matcher.load(nlp.path / 'vocab', nlp.vocab)
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