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Try to fix python3.5 serialization
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e262e8d942
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@ -370,7 +370,7 @@ class Tagger(Pipe):
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def __init__(self, vocab, model=True, **cfg):
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self.vocab = vocab
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self.model = model
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self.cfg = dict(cfg)
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self.cfg = OrderedDict(sorted(cfg.items()))
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self.cfg.setdefault('cnn_maxout_pieces', 2)
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self.cfg.setdefault('pretrained_dims',
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self.vocab.vectors.data.shape[1])
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@ -469,7 +469,7 @@ class Tagger(Pipe):
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def begin_training(self, gold_tuples=tuple(), pipeline=None, sgd=None):
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orig_tag_map = dict(self.vocab.morphology.tag_map)
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new_tag_map = {}
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new_tag_map = OrderedDict()
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for raw_text, annots_brackets in gold_tuples:
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for annots, brackets in annots_brackets:
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ids, words, tags, heads, deps, ents = annots
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@ -533,8 +533,9 @@ class Tagger(Pipe):
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serialize['model'] = self.model.to_bytes
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serialize['vocab'] = self.vocab.to_bytes
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tag_map = OrderedDict(sorted(self.vocab.morphology.item()))
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serialize['tag_map'] = lambda: msgpack.dumps(
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self.vocab.morphology.tag_map, use_bin_type=True, encoding='utf8')
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tag_map, use_bin_type=True, encoding='utf8')
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return util.to_bytes(serialize, exclude)
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def from_bytes(self, bytes_data, **exclude):
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@ -565,12 +566,11 @@ class Tagger(Pipe):
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def to_disk(self, path, **exclude):
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self.cfg['pretrained_dims'] = self.vocab.vectors.data.shape[1]
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tag_map = OrderedDict(sorted(self.vocab.morphology.item()))
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serialize = OrderedDict((
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('vocab', lambda p: self.vocab.to_disk(p)),
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('tag_map', lambda p: p.open('wb').write(msgpack.dumps(
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self.vocab.morphology.tag_map,
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use_bin_type=True,
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encoding='utf8'))),
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tag_map, use_bin_type=True, encoding='utf8'))),
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('model', lambda p: p.open('wb').write(self.model.to_bytes())),
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('cfg', lambda p: p.open('w').write(json_dumps(self.cfg)))
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))
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