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+ cdec cfg 'test/example/cdec.ini'
+feature: WordPenalty (no config parameters)
+State is 0 bytes for feature WordPenalty
+feature: KLanguageModel (with config parameters 'test/example/nc-wmt11.en.srilm.gz')
+Loading the LM will be faster if you build a binary file.
+Reading test/example/nc-wmt11.en.srilm.gz
+----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100
+****************************************************************************************************
+Loaded 5-gram KLM from test/example/nc-wmt11.en.srilm.gz (MapSize=49581)
+State is 98 bytes for feature KLanguageModel test/example/nc-wmt11.en.srilm.gz
+feature: RuleIdentityFeatures (no config parameters)
+State is 0 bytes for feature RuleIdentityFeatures
+feature: RuleNgramFeatures (no config parameters)
+State is 0 bytes for feature RuleNgramFeatures
+feature: RuleShape (no config parameters)
+ Example feature: Shape_S00000_T00000
+State is 0 bytes for feature RuleShape
+Seeding random number sequence to 380245307
+
+dtrain
+Parameters:
+ k 100
+ N 4
+ T 3
+ scorer 'stupid_bleu'
+ sample from 'kbest'
+ filter 'uniq'
+ learning rate 0.0001
+ gamma 0
+ pairs 'XYX'
+ hi lo 0.1
+ pair threshold 0
+ select weights 'VOID'
+ l1 reg 0 'none'
+ cdec cfg 'test/example/cdec.ini'
+ input 'test/example/nc-wmt11.1k.gz'
+ output '-'
+ stop_after 20
+(a dot represents 10 inputs)
+Iteration #1 of 3.
+ .. 20
+Stopping after 20 input sentences.
+WEIGHTS
+ Glue = -0.1015
+ WordPenalty = -0.0152
+ LanguageModel = +0.21493
+ LanguageModel_OOV = -0.3257
+ PhraseModel_0 = -0.050844
+ PhraseModel_1 = +0.25074
+ PhraseModel_2 = +0.27944
+ PhraseModel_3 = -0.038384
+ PhraseModel_4 = -0.12041
+ PhraseModel_5 = +0.1047
+ PhraseModel_6 = -0.1289
+ PassThrough = -0.3094
+ ---
+ 1best avg score: 0.17508 (+0.17508)
+ 1best avg model score: -1.2392 (-1.2392)
+ avg # pairs: 1329.8
+ avg # rank err: 649.1
+ avg # margin viol: 677.5
+ non0 feature count: 874
+ avg list sz: 88.6
+ avg f count: 85.643
+(time 0.25 min, 0.75 s/S)
+
+Iteration #2 of 3.
+ .. 20
+WEIGHTS
+ Glue = -0.0792
+ WordPenalty = -0.056198
+ LanguageModel = +0.31038
+ LanguageModel_OOV = -0.4011
+ PhraseModel_0 = +0.072188
+ PhraseModel_1 = +0.11473
+ PhraseModel_2 = +0.049774
+ PhraseModel_3 = -0.18448
+ PhraseModel_4 = -0.12092
+ PhraseModel_5 = +0.1599
+ PhraseModel_6 = -0.0606
+ PassThrough = -0.3848
+ ---
+ 1best avg score: 0.24015 (+0.065075)
+ 1best avg model score: -10.131 (-8.8914)
+ avg # pairs: 1324.7
+ avg # rank err: 558.65
+ avg # margin viol: 752.85
+ non0 feature count: 1236
+ avg list sz: 84.9
+ avg f count: 88.306
+(time 0.22 min, 0.65 s/S)
+
+Iteration #3 of 3.
+ .. 20
+WEIGHTS
+ Glue = -0.051
+ WordPenalty = -0.077956
+ LanguageModel = +0.33699
+ LanguageModel_OOV = -0.4726
+ PhraseModel_0 = +0.040228
+ PhraseModel_1 = +0.18
+ PhraseModel_2 = +0.15618
+ PhraseModel_3 = -0.098908
+ PhraseModel_4 = -0.036555
+ PhraseModel_5 = +0.1619
+ PhraseModel_6 = +0.0078
+ PassThrough = -0.4563
+ ---
+ 1best avg score: 0.25527 (+0.015113)
+ 1best avg model score: -13.906 (-3.7756)
+ avg # pairs: 1356.3
+ avg # rank err: 562.1
+ avg # margin viol: 757.35
+ non0 feature count: 1482
+ avg list sz: 86.65
+ avg f count: 87.475
+(time 0.23 min, 0.7 s/S)
+
+Writing weights file to '-' ...
+done
+
+---
+Best iteration: 3 [SCORE 'stupid_bleu'=0.25527].
+This took 0.7 min.