CDSCL/debug_note.txt at master · siegfang/CDSCL · GitHub

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SET VS90COMNTOOLS=%VS100COMNTOOLS%

python clscl_train.py en de Z:/DataDeport/cls-acl10-processed/en/books/train.processed Z:/DataDeport/cls-acl10-processed/en/books/unlabeled.processed Z:/DataDeport/cls-acl10-processed/de/books/unlabeled.processed Z:/DataDeport/cls-acl10-processed/dict/en_de_dict.txt model.bz2 --phi 30 --max-unlabeled=50000 -k 100 -m 450 --strategy=parallel > cmd_res.txt

python clscl_train.py en de Z:/DataDeport/cls-acl10-processed/en/books/train.processed Z:/DataDeport/cls-acl10-processed/en/books/unlabeled.processed Z:/DataDeport/cls-acl10-processed/de/books/unlabeled.processed Z:/DataDeport/cls-acl10-processed/dict/en_de_dict.txt model.bz2 --phi 30 --max-unlabeled=50000 -k 100 -m 450 --strategy=serial > cmd_res.txt

|V_S| = 64682
|V_T| = 106024
|V| = 170706
|s_train| = 2000
|s_unlabeled| = 50000
|t_unlabeled| = 50000
debug: DictTranslator contains 5012 translations.
mutualinformation took 5.624 sec
select_pivots took 7.197 sec
|pivots| = 450
create_inverted_index took 59.353 sec
Run joblib.Parallel
[Parallel(n_jobs=-1)]: Done   1 out of 450 |elapsed:    9.1s remaining: 67.8min
[Parallel(n_jobs=-1)]: Done   5 out of 450 |elapsed:   15.2s remaining: 22.6min
[..]
[Parallel(n_jobs=-1)]: Done 449 out of 450 |elapsed: 14.5min remaining:    1.9s
train_aux_classifiers took 881.803 sec
density: 0.1154
Ut.shape = (100,170706)
learn took 903.588 sec
project took 175.483 sec

python clscl_predict.py Z:/DataDeport/cls-acl10-processed/en/books/train.processed model.bz2 Z:/DataDeport/cls-acl10-processed/de/books/test.processed

|V_S| = 64682
|V_T| = 106024
|V| = 170706
load took 0.681 sec
load took 0.659 sec
classes = {negative,positive}
project took 2.498 sec
project took 2.716 sec
project took 2.275 sec
project took 2.492 sec
ACC: 83.05

python clscl_train.py en de Z:/DataDeport/cls-acl10-processed/en/books/train.processed Z:/DataDeport/cls-acl10-processed/en/books/unlabeled.processed Z:/DataDeport/cls-acl10-processed/de/books/unlabeled.processed Z:\DataDeport\cls-acl10-unprocessed\en\books\mymodel Z:\DataDeport\cls-acl10-unprocessed\de\books\mymodel Z:/DataDeport/cls-acl10-processed/dict/en_de_dict.txt model.bz2 --phi 30 --max-unlabeled=50000 -k 100 -m 450 --strategy=parallel --n-jobs=2


en de /Users/fangy/data/cls-acl10-processed/en/books/train.processed
/Users/fangy/data/cls-acl10-processed/en/books/unlabeled.processed
/Users/fangy/data/cls-acl10-processed/de/books/unlabeled.processed
/Users/fangy/data/cl14-unprocessed/en/books/mymodel
/Users/fangy/data/cl14-unprocessed/de/books/mymodel
/Users/fangy/data/cls-acl10-processed/dict/en_de_dict.txt
model.bz2 --phi 30 --max-unlabeled=500 -k 100 -m 450 --strategy=serial --n-jobs=2

|V_S| = 7107
|V_T| = 4116
|V| = 11223
classes = {negative,positive}
|s_train| = 2000
|s_unlabeled| = 500
|t_unlabeled| = 500
debug: DictTranslator contains 5012 translations.
mutualinformation took 3.459 sec
select_pivots took 3.538 sec
|pivots| = 137
|V| = 11223
create_inverted_index took 0.303 sec
Run joblib.Parallel
/Users/fangy/code/CLSCL/nut2/gensim/word2vec.py:641: UnicodeWarning: Unicode equal comparison failed to convert both arguments to Unicode - interpreting them as being unequal
  return word in self.vocab
instance2vec took 2.130 sec
[Parallel(n_jobs=2)]: Done   1 out of 137 |elapsed:    5.0s remaining: 11.2min
[Parallel(n_jobs=2)]: Done   3 out of 137 |elapsed:   14.8s remaining: 11.1min
...
[Parallel(n_jobs=2)]: Done 135 out of 137 |elapsed: 10.7min remaining:    9.5s
[Parallel(n_jobs=2)]: Done 137 out of 137 |elapsed: 10.9min remaining:    0.0s
train_aux_classifiers took 659.068 sec
density of W: 0.00842314
Compute SVD w/o feature type splits
W.nnz: 12951
W.shape: (11223, 137)
Ut.shape (100, 11223)
Spectrum: 3.0326 - 120.8000
________________________________________________________________________________
thetat.shape (11223, 100)
dim of embedding: 100
learn took 659.096 sec
project took 2.630 sec
project took 0.639 sec
project took 0.617 sec
project took 10.652 sec

--max-unlabeled 50000

density of W: 0.00044278
Compute SVD w/o feature type splits
W.nnz: 34013
W.shape: (170706, 450)
Ut.shape (100, 170706)
Spectrum: 7.0676 - 97.1676
________________________________________________________________________________
thetat.shape (170706, 100)
dim of embedding: 100
learn took 8805.271 sec