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Improve beam search defaults

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Matthew Honnibal 2019-03-17 21:47:45 +01:00
parent 226db621d0
commit 0a4b074184
1 changed files with 2 additions and 2 deletions
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spacy/syntax/nn_parser.pyx
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@ -402,11 +402,11 @@ cdef class Parser:
multitask.update(docs, golds, drop=drop, sgd=sgd) multitask.update(docs, golds, drop=drop, sgd=sgd)
# The probability we use beam update, instead of falling back to # The probability we use beam update, instead of falling back to
# a greedy update # a greedy update
beam_update_prob = self.cfg.get('beam_update_prob', 1.0) beam_update_prob = self.cfg.get('beam_update_prob', 0.5)
if self.cfg.get('beam_width', 1) >= 2 and numpy.random.random() < beam_update_prob: if self.cfg.get('beam_width', 1) >= 2 and numpy.random.random() < beam_update_prob:
return self.update_beam(docs, golds, self.cfg.get('beam_width', 1), return self.update_beam(docs, golds, self.cfg.get('beam_width', 1),
drop=drop, sgd=sgd, losses=losses, drop=drop, sgd=sgd, losses=losses,
beam_density=self.cfg.get('beam_density', 0.0)) beam_density=self.cfg.get('beam_density', 0.001))
# Chop sequences into lengths of this many transitions, to make the # Chop sequences into lengths of this many transitions, to make the
# batch uniform length. # batch uniform length.
cut_gold = numpy.random.choice(range(20, 100)) cut_gold = numpy.random.choice(range(20, 100))