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Revert changes to tagger and parser for thinc 6
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@ -255,10 +255,10 @@ cdef class Parser:
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cdef weight_t loss = 0
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cdef Transition action
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while not stcls.is_final():
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self.model.set_featuresC(eg.c, stcls.c)
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self.model.set_featuresC(&eg.c, stcls.c)
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self.moves.set_costs(eg.c.is_valid, eg.c.costs, stcls, gold)
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self.model.set_scoresC(eg.c.scores, eg.c.features, eg.c.nr_feat)
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self.model.updateC(eg.c)
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self.model.updateC(&eg.c)
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guess = VecVec.arg_max_if_true(eg.c.scores, eg.c.is_valid, eg.c.nr_class)
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action = self.moves.c[eg.guess]
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@ -343,7 +343,7 @@ cdef class StepwiseState:
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def predict(self):
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self.eg.reset()
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self.parser.model.set_featuresC(self.eg.c, self.stcls.c)
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self.parser.model.set_featuresC(&self.eg.c, self.stcls.c)
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self.parser.moves.set_valid(self.eg.c.is_valid, self.stcls.c)
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self.parser.model.set_scoresC(self.eg.c.scores,
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self.eg.c.features, self.eg.c.nr_feat)
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@ -192,7 +192,7 @@ cdef class Tagger:
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nr_feat=self.model.nr_feat)
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for i in range(tokens.length):
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if tokens.c[i].pos == 0:
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self.model.set_featuresC(eg.c, tokens.c, i)
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self.model.set_featuresC(&eg.c, tokens.c, i)
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self.model.set_scoresC(eg.c.scores,
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eg.c.features, eg.c.nr_feat)
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guess = VecVec.arg_max_if_true(eg.c.scores, eg.c.is_valid, eg.c.nr_class)
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@ -244,11 +244,11 @@ cdef class Tagger:
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nr_class=self.vocab.morphology.n_tags,
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nr_feat=self.model.nr_feat)
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for i in range(tokens.length):
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self.model.set_featuresC(eg.c, tokens.c, i)
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self.model.set_featuresC(&eg.c, tokens.c, i)
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eg.costs = [ 1 if golds[i] not in (c, -1) else 0 for c in xrange(eg.nr_class) ]
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self.model.set_scoresC(eg.c.scores,
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eg.c.features, eg.c.nr_feat)
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self.model.updateC(eg.c)
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self.model.updateC(&eg.c)
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self.vocab.morphology.assign_tag_id(&tokens.c[i], eg.guess)
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