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Switch to single matmul for state layer

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Matthew Honnibal 2017-05-07 14:26:34 +02:00
parent 700979fb3c
commit 12039e80ca
1 changed files with 5 additions and 3 deletions
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8
spacy/_ml.py
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@ -1,5 +1,5 @@
from thinc.api import add, layerize, chain, clone, concatenate, with_flatten
from thinc.neural import Model, Maxout, Softmax, Affine
from thinc.neural import Model, ReLu, Maxout, Softmax, Affine
from thinc.neural._classes.hash_embed import HashEmbed
from thinc.neural._classes.convolution import ExtractWindow
@ -37,6 +37,7 @@ def build_debug_model(state2vec, width, depth, nr_class):
with Model.define_operators({'>>': chain, '**': clone}):
model = (
state2vec
#>> Maxout(width)
>> Maxout(nr_class)
)
return model
@ -64,8 +65,9 @@ def build_debug_state2vec(width, nr_vector=1000, nF=1, nB=0, nS=1, nL=2, nR=2):
def build_state2vec(nr_context_tokens, width, nr_vector=1000):
ops = Model.ops
with Model.define_operators({'|': concatenate, '+': add, '>>': chain}):
hiddens = [get_col(i) >> Maxout(width) for i in range(nr_context_tokens)]
model = get_token_vectors >> add(*hiddens)
#hiddens = [get_col(i) >> Maxout(width) for i in range(nr_context_tokens)]
features = [get_col(i) for i in range(nr_context_tokens)]
model = get_token_vectors >> concatenate(*features) >> ReLu(width)
return model