mirror of https://github.com/explosion/spaCy.git
Adjust dropout, depth and multi-task in parser
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@ -416,7 +416,9 @@ cdef class Parser:
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free(scores)
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free(token_ids)
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def update(self, docs_tokvecs, golds, drop=0., sgd=None):
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def update(self, docs_tokvecs, golds, drop=0., sgd=None, losses=None):
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if losses is not None and self.name not in losses:
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losses[self.name] = 0.
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docs, tokvec_lists = docs_tokvecs
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tokvecs = self.model[0].ops.flatten(tokvec_lists)
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if isinstance(docs, Doc) and isinstance(golds, GoldParse):
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@ -436,18 +438,20 @@ cdef class Parser:
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backprops = []
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d_tokvecs = state2vec.ops.allocate(tokvecs.shape)
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cdef float loss = 0.
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while len(todo) >= 3:
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while len(todo) >= 2:
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states, golds = zip(*todo)
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token_ids = self.get_token_ids(states)
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vector, bp_vector = state2vec.begin_update(token_ids, drop=0.0)
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mask = vec2scores.ops.get_dropout_mask(vector.shape, drop)
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vector *= mask
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if drop != 0:
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mask = vec2scores.ops.get_dropout_mask(vector.shape, drop)
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vector *= mask
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scores, bp_scores = vec2scores.begin_update(vector, drop=drop)
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d_scores = self.get_batch_loss(states, golds, scores)
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d_vector = bp_scores(d_scores, sgd=sgd)
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d_vector *= mask
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if drop != 0:
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d_vector *= mask
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if isinstance(self.model[0].ops, CupyOps) \
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and not isinstance(token_ids, state2vec.ops.xp.ndarray):
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@ -461,10 +465,12 @@ cdef class Parser:
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backprops.append((token_ids, d_vector, bp_vector))
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self.transition_batch(states, scores)
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todo = [st for st in todo if not st[0].is_final()]
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if len(backprops) >= 50:
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if len(backprops) >= 20:
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self._make_updates(d_tokvecs,
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backprops, sgd, cuda_stream)
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backprops = []
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if losses is not None:
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losses[self.name] += (d_scores**2).sum()
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if backprops:
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self._make_updates(d_tokvecs,
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backprops, sgd, cuda_stream)
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