Default to beam_update_prob 1
@@ -356,7 +356,7 @@ cdef class Parser:
losses.setdefault(self.name, 0.)
# The probability we use beam update, instead of falling back to
# a greedy update
- beam_update_prob = self.cfg.get('beam_update_prob', 0.5)
+ beam_update_prob = self.cfg.get('beam_update_prob', 1.0)
if self.cfg.get('beam_width', 1) >= 2 and numpy.random.random() < beam_update_prob:
return self.update_beam(docs, golds,
self.cfg['beam_width'],
@@ -391,7 +391,7 @@ cdef class Parser:
self.moves.preprocess_gold(gold)
model, finish_update = self.model.begin_update(docs, drop=drop)
states_d_scores, backprops, beams = _beam_utils.update_beam(
- self.moves, self.nr_feature, 500, states, golds, model.state2vec,
+ self.moves, self.nr_feature, 10000, states, golds, model.state2vec,
model.vec2scores, width, drop=drop, losses=losses)
for i, d_scores in enumerate(states_d_scores):
losses[self.name] += (d_scores**2).sum()
