From 10367981553bcf1b7361cdbb76bdb50ad9d06b6f Mon Sep 17 00:00:00 2001 From: Matthew Honnibal Date: Fri, 20 Oct 2017 16:24:16 +0200 Subject: [PATCH] Make parser consistent if maxout==1 --- spacy/syntax/nn_parser.pyx | 13 ++++++------- 1 file changed, 6 insertions(+), 7 deletions(-) diff --git a/spacy/syntax/nn_parser.pyx b/spacy/syntax/nn_parser.pyx index 465e4d877..f95d4e0cd 100644 --- a/spacy/syntax/nn_parser.pyx +++ b/spacy/syntax/nn_parser.pyx @@ -136,7 +136,8 @@ cdef class precompute_hiddens: return self.begin_update(X)[0] def begin_update(self, token_ids, drop=0.): - cdef np.ndarray state_vector = numpy.zeros((token_ids.shape[0], self.nO*self.nP), dtype='f') + cdef np.ndarray state_vector = numpy.zeros( + (token_ids.shape[0], self.nO, self.nP), dtype='f') # This is tricky, but (assuming GPU available); # - Input to forward on CPU # - Output from forward on CPU @@ -166,16 +167,13 @@ cdef class precompute_hiddens: mask = state_vector >= 0. state_vector *= mask else: - state_vector = state_vector.reshape( - (state_vector.shape[0], self.nO, self.nP)) state_vector, mask = self.ops.maxout(state_vector) def backprop_nonlinearity(d_best, sgd=None): if self.nP == 1: return d_best * mask else: - d_vector = self.ops.backprop_maxout(d_best, mask, self.nP) - return d_vector.reshape((d_vector.shape[0], self.nO*self.nP)) + return self.ops.backprop_maxout(d_best, mask, self.nP) return state_vector, backprop_nonlinearity @@ -266,8 +264,9 @@ cdef class Parser: tok2vec = Tok2Vec(token_vector_width, embed_size, pretrained_dims=cfg.get('pretrained_dims', 0)) tok2vec = chain(tok2vec, flatten) - lower = PrecomputableAffine(hidden_width * parser_maxout_pieces, - nF=cls.nr_feature, nI=token_vector_width) + lower = PrecomputableAffine(hidden_width, + nF=cls.nr_feature, nI=token_vector_width, + nP=parser_maxout_pieces) lower.nP = parser_maxout_pieces with Model.use_device('cpu'):