forked from zhezhaoa/ngram2vec
-
Notifications
You must be signed in to change notification settings - Fork 3
/
uni_bi.sh
95 lines (84 loc) · 4.51 KB
/
uni_bi.sh
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
#!/bin/sh
win=2
size=300
thr=100
sub=1e-5
iters=3
threads=10
negative=5
memsize=8.0
corpus=wiki2010.clean
output_path=outputs/uni_bi/win${win}
mkdir -p ${output_path}/sgns
mkdir -p ${output_path}/ppmi
mkdir -p ${output_path}/svd
mkdir -p ${output_path}/glove
python ngram2vec/corpus2vocab.py --ngram 2 --memory_size ${memsize} --min_count ${thr} ${corpus} ${output_path}/vocab
python ngram2vec/corpus2pairs.py --win ${win} --sub ${sub} --ngram_word 1 --ngram_context 2 --threads_num ${threads} --overlap ${corpus} ${output_path}/vocab ${output_path}/pairs
if [ -f "${output_path}/pairs" ]
then
rm ${output_path}/pairs
fi
for i in $(seq 0 $((${threads}-1)) )
do
cat ${output_path}/pairs_${i} >> ${output_path}/pairs
rm ${output_path}/pairs_${i}
done
python ngram2vec/pairs2vocab.py ${output_path}/pairs ${output_path}/words.vocab ${output_path}/contexts.vocab
#SGNS
./word2vecf/word2vecf -train ${output_path}/pairs -pow 0.75 -cvocab ${output_path}/contexts.vocab -wvocab ${output_path}/words.vocab -dumpcv ${output_path}/sgns/sgns.contexts -output ${output_path}/sgns/sgns.words -threads ${threads} -negative ${negative} -size ${size} -iters ${iters}
#SGNS evaluation
cp ${output_path}/words.vocab ${output_path}/sgns/sgns.words.vocab
cp ${output_path}/contexts.vocab ${output_path}/sgns/sgns.contexts.vocab
python ngram2vec/text2numpy.py ${output_path}/sgns/sgns.words
python ngram2vec/text2numpy.py ${output_path}/sgns/sgns.contexts
for dataset in testsets/analogy/google.txt testsets/analogy/semantic.txt testsets/analogy/syntactic.txt testsets/analogy/msr.txt
do
python ngram2vec/analogy_eval.py SGNS ${output_path}/sgns/sgns ${dataset}
done
for dataset in testsets/ws/ws353_similarity.txt testsets/ws/ws353_relatedness.txt testsets/ws/bruni_men.txt testsets/ws/radinsky_mturk.txt testsets/ws/luong_rare.txt testsets/ws/sim999.txt
do
python ngram2vec/ws_eval.py SGNS ${output_path}/sgns/sgns ${dataset}
done
python ngram2vec/pairs2counts.py --memory_size ${memsize} ${output_path}/pairs ${output_path}/words.vocab ${output_path}/contexts.vocab ${output_path}/counts
#PPMI
python ngram2vec/counts2ppmi.py ${output_path}/words.vocab ${output_path}/contexts.vocab ${output_path}/counts ${output_path}/ppmi/ppmi
#PPMI evaluation
cp ${output_path}/words.vocab ${output_path}/ppmi/ppmi.words.vocab
cp ${output_path}/contexts.vocab ${output_path}/ppmi/ppmi.contexts.vocab
for dataset in testsets/analogy/google.txt testsets/analogy/semantic.txt testsets/analogy/syntactic.txt testsets/analogy/msr.txt
do
python ngram2vec/analogy_eval.py PPMI ${output_path}/ppmi/ppmi ${dataset}
done
for dataset in testsets/ws/ws353_similarity.txt testsets/ws/ws353_relatedness.txt testsets/ws/bruni_men.txt testsets/ws/radinsky_mturk.txt testsets/ws/luong_rare.txt testsets/ws/sim999.txt
do
python ngram2vec/ws_eval.py PPMI ${output_path}/ppmi/ppmi ${dataset}
done
#SVD
python ngram2vec/ppmi2svd.py ${output_path}/ppmi/ppmi ${output_path}/svd/svd
#SVD evaluation
cp ${output_path}/words.vocab ${output_path}/svd/svd.words.vocab
cp ${output_path}/contexts.vocab ${output_path}/svd/svd.contexts.vocab
for dataset in testsets/analogy/google.txt testsets/analogy/semantic.txt testsets/analogy/syntactic.txt testsets/analogy/msr.txt
do
python ngram2vec/analogy_eval.py SVD ${output_path}/svd/svd ${dataset}
done
for dataset in testsets/ws/ws353_similarity.txt testsets/ws/ws353_relatedness.txt testsets/ws/bruni_men.txt testsets/ws/radinsky_mturk.txt testsets/ws/luong_rare.txt testsets/ws/sim999.txt
do
python ngram2vec/ws_eval.py SVD ${output_path}/svd/svd ${dataset}
done
#GloVe
python ngram2vec/counts2shuf.py ${output_path}/counts ${output_path}/counts.shuf
python ngram2vec/counts2bin.py ${output_path}/counts.shuf ${output_path}/counts.shuf.bin
./GloVe/build/glove -save-file ${output_path}/glove/glove.words -threads ${threads} -input-file ${output_path}/counts.shuf.bin -vector-size ${size} -words-file ${output_path}/words.vocab -contexts-file ${output_path}/contexts.vocab
cp ${output_path}/words.vocab ${output_path}/glove/glove.words.vocab
python ngram2vec/text2numpy.py ${output_path}/glove/glove.words
#GloVe evaluation
for dataset in testsets/analogy/google.txt testsets/analogy/semantic.txt testsets/analogy/syntactic.txt testsets/analogy/msr.txt
do
python ngram2vec/analogy_eval.py GLOVE ${output_path}/glove/glove ${dataset}
done
for dataset in testsets/ws/ws353_similarity.txt testsets/ws/ws353_relatedness.txt testsets/ws/bruni_men.txt testsets/ws/radinsky_mturk.txt testsets/ws/luong_rare.txt testsets/ws/sim999.txt
do
python ngram2vec/ws_eval.py GLOVE ${output_path}/glove/glove ${dataset}
done