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Pass documents to tensorizer, not 'features'

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Matthew Honnibal 2017-09-16 12:46:36 -05:00
parent 84e637e2e6
commit e37a50a436
1 changed files with 1 additions and 2 deletions
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spacy/language.py
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@ -304,13 +304,12 @@ class Language(object):
self._optimizer = Adam(Model.ops, 0.001) self._optimizer = Adam(Model.ops, 0.001)
sgd = self._optimizer sgd = self._optimizer
tok2vec = self.pipeline[0] tok2vec = self.pipeline[0]
feats = tok2vec.doc2feats(docs)
grads = {} grads = {}
def get_grads(W, dW, key=None): def get_grads(W, dW, key=None):
grads[key] = (W, dW) grads[key] = (W, dW)
pipes = list(self.pipeline[1:]) pipes = list(self.pipeline[1:])
random.shuffle(pipes) random.shuffle(pipes)
tokvecses, bp_tokvecses = tok2vec.model.begin_update(feats, drop=drop) tokvecses, bp_tokvecses = tok2vec.model.begin_update(docs, drop=drop)
all_d_tokvecses = [tok2vec.model.ops.allocate(tv.shape) for tv in tokvecses] all_d_tokvecses = [tok2vec.model.ops.allocate(tv.shape) for tv in tokvecses]
for proc in pipes: for proc in pipes:
if not hasattr(proc, 'update'): if not hasattr(proc, 'update'):