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Fix loading models with pretrained vectors
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@ -636,11 +636,11 @@ class Language(object):
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"""
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path = util.ensure_path(path)
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deserializers = OrderedDict((
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('vocab', lambda p: self.vocab.from_disk(p)),
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('meta.json', lambda p: self.meta.update(util.read_json(p))),
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('vocab', lambda p: (
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self.vocab.from_disk(p) and _fix_pretrained_vectors_name(self))),
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('tokenizer', lambda p: self.tokenizer.from_disk(p, vocab=False)),
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('meta.json', lambda p: self.meta.update(util.read_json(p)))
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))
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_fix_pretrained_vectors_name(self)
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for name, proc in self.pipeline:
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if name in disable:
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continue
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@ -682,11 +682,11 @@ class Language(object):
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RETURNS (Language): The `Language` object.
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"""
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deserializers = OrderedDict((
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('vocab', lambda b: self.vocab.from_bytes(b)),
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('meta', lambda b: self.meta.update(ujson.loads(b))),
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('vocab', lambda b: (
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self.vocab.from_bytes(b) and _fix_pretrained_vectors_name(self))),
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('tokenizer', lambda b: self.tokenizer.from_bytes(b, vocab=False)),
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('meta', lambda b: self.meta.update(ujson.loads(b)))
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))
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_fix_pretrained_vectors_name(self)
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for i, (name, proc) in enumerate(self.pipeline):
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if name in disable:
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continue
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@ -708,12 +708,12 @@ def _fix_pretrained_vectors_name(nlp):
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nlp.vocab.vectors.name = vectors_name
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else:
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raise ValueError(Errors.E092)
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link_vectors_to_models(nlp.vocab)
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for name, proc in nlp.pipeline:
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if not hasattr(proc, 'cfg'):
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continue
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if proc.cfg.get('pretrained_dims'):
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assert nlp.vocab.vectors.name
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proc.cfg['pretrained_vectors'] = nlp.vocab.vectors.name
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proc.cfg.setdefault('deprecation_fixes', {})
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proc.cfg['deprecation_fixes']['vectors_name'] = nlp.vocab.vectors.name
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class DisabledPipes(list):
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