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Fix training for new labels
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@ -151,7 +151,6 @@ cdef class Parser:
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if isinstance(labels, dict):
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labels = list(sorted(labels.keys()))
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cfg['actions'][action_name] = labels
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print(cfg['actions'])
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self = cls(vocab, TransitionSystem=TransitionSystem, model=None, **cfg)
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if (path / 'model').exists():
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self.model.load(str(path / 'model'))
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@ -187,6 +186,11 @@ cdef class Parser:
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self.model.learn_rate = cfg.get('learn_rate', 0.001)
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self.cfg = cfg
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# TODO: This is a pretty hacky fix to the problem of adding more
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# labels. The issue is they come in out of order, if labels are
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# added during training
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for label in cfg.get('extra_labels', []):
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self.add_label(label)
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def __reduce__(self):
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return (Parser, (self.vocab, self.moves, self.model), None, None)
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