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

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This commit is contained in:
Matthew Honnibal 2017-08-18 22:38:28 +02:00
parent de7e8703e3
commit fe90dfc390
1 changed files with 4 additions and 3 deletions
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7
spacy/_ml.py
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@ -9,7 +9,7 @@ import cytoolz
from thinc.neural._classes.convolution import ExtractWindow
from thinc.neural._classes.static_vectors import StaticVectors
from thinc.neural._classes.batchnorm import BatchNorm
from thinc.neural._classes.batchnorm import BatchNorm as BN
from thinc.neural._classes.layernorm import LayerNorm as LN
from thinc.neural._classes.resnet import Residual
from thinc.neural import ReLu
@ -22,6 +22,7 @@ from thinc.neural.pooling import Pooling, max_pool, mean_pool, sum_pool
from thinc.neural._classes.attention import ParametricAttention
from thinc.linear.linear import LinearModel
from thinc.api import uniqued, wrap, flatten_add_lengths
from thinc.neural._classes.rnn import BiLSTM
from .attrs import ID, ORTH, LOWER, NORM, PREFIX, SUFFIX, SHAPE, TAG, DEP
@ -229,14 +230,14 @@ def Tok2Vec(width, embed_size, preprocess=None):
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')
embed = (norm | prefix | suffix | shape ) >> Maxout(width, width*4, pieces=3)
embed = (norm | prefix | suffix | shape ) >> LN(Maxout(width, width*4, pieces=3))
tok2vec = (
with_flatten(
asarray(Model.ops, dtype='uint64')
>> uniqued(embed, column=5)
>> drop_layer(
Residual(
(ExtractWindow(nW=1) >> ReLu(width, width*3))
(ExtractWindow(nW=1) >> BN(Maxout(width, width*3)))
)
) ** 4, pad=4
)