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Restore changes from nn-beam-parser to spacy/_ml

This commit is contained in:
Matthew Honnibal 2017-08-18 22:24:46 +02:00
parent 5f81d700ff
commit ce321b0322
1 changed files with 3 additions and 3 deletions
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6
spacy/_ml.py
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@ -9,7 +9,7 @@ import cytoolz
from thinc.neural._classes.convolution import ExtractWindow from thinc.neural._classes.convolution import ExtractWindow
from thinc.neural._classes.static_vectors import StaticVectors from thinc.neural._classes.static_vectors import StaticVectors
from thinc.neural._classes.batchnorm import BatchNorm as BN from thinc.neural._classes.batchnorm import BatchNorm
from thinc.neural._classes.layernorm import LayerNorm as LN from thinc.neural._classes.layernorm import LayerNorm as LN
from thinc.neural._classes.resnet import Residual from thinc.neural._classes.resnet import Residual
from thinc.neural import ReLu from thinc.neural import ReLu
@ -229,14 +229,14 @@ def Tok2Vec(width, embed_size, preprocess=None):
suffix = get_col(cols.index(SUFFIX)) >> HashEmbed(width, embed_size//2, name='embed_suffix') suffix = get_col(cols.index(SUFFIX)) >> HashEmbed(width, embed_size//2, name='embed_suffix')
shape = get_col(cols.index(SHAPE)) >> HashEmbed(width, embed_size//2, name='embed_shape') shape = get_col(cols.index(SHAPE)) >> HashEmbed(width, embed_size//2, name='embed_shape')
embed = (norm | prefix | suffix | shape ) >> LN(Maxout(width, width*4, pieces=3)) embed = (norm | prefix | suffix | shape ) >> Maxout(width, width*4, pieces=3)
tok2vec = ( tok2vec = (
with_flatten( with_flatten(
asarray(Model.ops, dtype='uint64') asarray(Model.ops, dtype='uint64')
>> uniqued(embed, column=5) >> uniqued(embed, column=5)
>> drop_layer( >> drop_layer(
Residual( Residual(
(ExtractWindow(nW=1) >> BN(Maxout(width, width*3))) (ExtractWindow(nW=1) >> ReLu(width, width*3))
) )
) ** 4, pad=4 ) ** 4, pad=4
) )