dtrain: removed old stuff

14 files changed, 0 insertions, 341 deletions

diff --git a/training/dtrain/examples/parallelized/work/out.0.0 b/training/dtrain/examples/parallelized/work/out.0.0
deleted file mode 100644
index c559dd4d..00000000
--- a/training/dtrain/examples/parallelized/work/out.0.0
+++ /dev/null
@@ -1,62 +0,0 @@
-                cdec cfg 'cdec.ini'
-Loading the LM will be faster if you build a binary file.
-Reading ../standard//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
-****************************************************************************************************
-Seeding random number sequence to 405292278
-
-dtrain
-Parameters:
-                       k 100
-                       N 4
-                       T 1
-                  scorer 'stupid_bleu'
-             sample from 'kbest'
-                  filter 'uniq'
-           learning rate 0.0001
-                   gamma 0
-             loss margin 1
-       faster perceptron 0
-                   pairs 'XYX'
-                   hi lo 0.1
-          pair threshold 0
-          select weights 'last'
-                  l1 reg 0 'none'
-               max pairs 4294967295
-                cdec cfg 'cdec.ini'
-                   input 'work/shard.0.0.in'
-                    refs 'work/shard.0.0.refs'
-                  output 'work/weights.0.0'
-(a dot represents 10 inputs)
-Iteration #1 of 1.
-  5
-WEIGHTS
-              Glue = +0.2663
-       WordPenalty = -0.0079042
-     LanguageModel = +0.44782
- LanguageModel_OOV = -0.0401
-     PhraseModel_0 = -0.193
-     PhraseModel_1 = +0.71321
-     PhraseModel_2 = +0.85196
-     PhraseModel_3 = -0.43986
-     PhraseModel_4 = -0.44803
-     PhraseModel_5 = -0.0538
-     PhraseModel_6 = -0.1788
-       PassThrough = -0.1477
-        ---
-       1best avg score: 0.17521 (+0.17521)
- 1best avg model score: 21.556 (+21.556)
-           avg # pairs: 1671.2
-        avg # rank err: 1118.6
-     avg # margin viol: 552.6
-    non0 feature count: 12
-           avg list sz: 100
-           avg f count: 11.32
-(time 0.35 min, 4.2 s/S)
-
-Writing weights file to 'work/weights.0.0' ...
-done
-
----
-Best iteration: 1 [SCORE 'stupid_bleu'=0.17521].
-This took 0.35 min.
diff --git a/training/dtrain/examples/parallelized/work/out.0.1 b/training/dtrain/examples/parallelized/work/out.0.1
deleted file mode 100644
index 8bc7ea9c..00000000
--- a/training/dtrain/examples/parallelized/work/out.0.1
+++ /dev/null
@@ -1,63 +0,0 @@
-                cdec cfg 'cdec.ini'
-Loading the LM will be faster if you build a binary file.
-Reading ../standard//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
-****************************************************************************************************
-Seeding random number sequence to 43859692
-
-dtrain
-Parameters:
-                       k 100
-                       N 4
-                       T 1
-                  scorer 'stupid_bleu'
-             sample from 'kbest'
-                  filter 'uniq'
-           learning rate 0.0001
-                   gamma 0
-             loss margin 1
-       faster perceptron 0
-                   pairs 'XYX'
-                   hi lo 0.1
-          pair threshold 0
-          select weights 'last'
-                  l1 reg 0 'none'
-               max pairs 4294967295
-                cdec cfg 'cdec.ini'
-                   input 'work/shard.0.0.in'
-                    refs 'work/shard.0.0.refs'
-                  output 'work/weights.0.1'
-              weights in 'work/weights.0'
-(a dot represents 10 inputs)
-Iteration #1 of 1.
-  5
-WEIGHTS
-              Glue = -0.2699
-       WordPenalty = +0.080605
-     LanguageModel = -0.026572
- LanguageModel_OOV = -0.30025
-     PhraseModel_0 = -0.32076
-     PhraseModel_1 = +0.67451
-     PhraseModel_2 = +0.92
-     PhraseModel_3 = -0.36402
-     PhraseModel_4 = -0.592
-     PhraseModel_5 = -0.0269
-     PhraseModel_6 = -0.28755
-       PassThrough = -0.33285
-        ---
-       1best avg score: 0.26638 (+0.26638)
- 1best avg model score: 53.197 (+53.197)
-           avg # pairs: 2028.6
-        avg # rank err: 998.2
-     avg # margin viol: 918.8
-    non0 feature count: 12
-           avg list sz: 100
-           avg f count: 10.496
-(time 0.35 min, 4.2 s/S)
-
-Writing weights file to 'work/weights.0.1' ...
-done
-
----
-Best iteration: 1 [SCORE 'stupid_bleu'=0.26638].
-This took 0.35 min.
diff --git a/training/dtrain/examples/parallelized/work/out.1.0 b/training/dtrain/examples/parallelized/work/out.1.0
deleted file mode 100644
index 65d1e7dc..00000000
--- a/training/dtrain/examples/parallelized/work/out.1.0
+++ /dev/null
@@ -1,62 +0,0 @@
-                cdec cfg 'cdec.ini'
-Loading the LM will be faster if you build a binary file.
-Reading ../standard//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
-****************************************************************************************************
-Seeding random number sequence to 4126799437
-
-dtrain
-Parameters:
-                       k 100
-                       N 4
-                       T 1
-                  scorer 'stupid_bleu'
-             sample from 'kbest'
-                  filter 'uniq'
-           learning rate 0.0001
-                   gamma 0
-             loss margin 1
-       faster perceptron 0
-                   pairs 'XYX'
-                   hi lo 0.1
-          pair threshold 0
-          select weights 'last'
-                  l1 reg 0 'none'
-               max pairs 4294967295
-                cdec cfg 'cdec.ini'
-                   input 'work/shard.1.0.in'
-                    refs 'work/shard.1.0.refs'
-                  output 'work/weights.1.0'
-(a dot represents 10 inputs)
-Iteration #1 of 1.
-  5
-WEIGHTS
-              Glue = -0.3815
-       WordPenalty = +0.20064
-     LanguageModel = +0.95304
- LanguageModel_OOV = -0.264
-     PhraseModel_0 = -0.22362
-     PhraseModel_1 = +0.12254
-     PhraseModel_2 = +0.26328
-     PhraseModel_3 = +0.38018
-     PhraseModel_4 = -0.48654
-     PhraseModel_5 = +0
-     PhraseModel_6 = -0.3645
-       PassThrough = -0.2216
-        ---
-       1best avg score: 0.10863 (+0.10863)
- 1best avg model score: -4.9841 (-4.9841)
-           avg # pairs: 1345.4
-        avg # rank err: 822.4
-     avg # margin viol: 501
-    non0 feature count: 11
-           avg list sz: 100
-           avg f count: 11.814
-(time 0.43 min, 5.2 s/S)
-
-Writing weights file to 'work/weights.1.0' ...
-done
-
----
-Best iteration: 1 [SCORE 'stupid_bleu'=0.10863].
-This took 0.43333 min.
diff --git a/training/dtrain/examples/parallelized/work/out.1.1 b/training/dtrain/examples/parallelized/work/out.1.1
deleted file mode 100644
index f479fbbc..00000000
--- a/training/dtrain/examples/parallelized/work/out.1.1
+++ /dev/null
@@ -1,63 +0,0 @@
-                cdec cfg 'cdec.ini'
-Loading the LM will be faster if you build a binary file.
-Reading ../standard//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
-****************************************************************************************************
-Seeding random number sequence to 2112412848
-
-dtrain
-Parameters:
-                       k 100
-                       N 4
-                       T 1
-                  scorer 'stupid_bleu'
-             sample from 'kbest'
-                  filter 'uniq'
-           learning rate 0.0001
-                   gamma 0
-             loss margin 1
-       faster perceptron 0
-                   pairs 'XYX'
-                   hi lo 0.1
-          pair threshold 0
-          select weights 'last'
-                  l1 reg 0 'none'
-               max pairs 4294967295
-                cdec cfg 'cdec.ini'
-                   input 'work/shard.1.0.in'
-                    refs 'work/shard.1.0.refs'
-                  output 'work/weights.1.1'
-              weights in 'work/weights.0'
-(a dot represents 10 inputs)
-Iteration #1 of 1.
-  5
-WEIGHTS
-              Glue = -0.3178
-       WordPenalty = +0.11092
-     LanguageModel = +0.17269
- LanguageModel_OOV = -0.13485
-     PhraseModel_0 = -0.45371
-     PhraseModel_1 = +0.38789
-     PhraseModel_2 = +0.75311
-     PhraseModel_3 = -0.38163
-     PhraseModel_4 = -0.58817
-     PhraseModel_5 = -0.0269
-     PhraseModel_6 = -0.27315
-       PassThrough = -0.16745
-        ---
-       1best avg score: 0.13169 (+0.13169)
- 1best avg model score: 24.226 (+24.226)
-           avg # pairs: 1951.2
-        avg # rank err: 985.4
-     avg # margin viol: 951
-    non0 feature count: 12
-           avg list sz: 100
-           avg f count: 11.224
-(time 0.45 min, 5.4 s/S)
-
-Writing weights file to 'work/weights.1.1' ...
-done
-
----
-Best iteration: 1 [SCORE 'stupid_bleu'=0.13169].
-This took 0.45 min.
diff --git a/training/dtrain/examples/parallelized/work/shard.0.0.in b/training/dtrain/examples/parallelized/work/shard.0.0.in
deleted file mode 100644
index 92f9c78e..00000000
--- a/training/dtrain/examples/parallelized/work/shard.0.0.in
+++ /dev/null
@@ -1,5 +0,0 @@
-<seg grammar="grammar/grammar.out.0.gz" id="0">europas nach rassen geteiltes haus</seg>
-<seg grammar="grammar/grammar.out.1.gz" id="1">ein gemeinsames merkmal aller extremen rechten in europa ist ihr rassismus und die tatsache , daß sie das einwanderungsproblem als politischen hebel benutzen .</seg>
-<seg grammar="grammar/grammar.out.2.gz" id="2">der lega nord in italien , der vlaams block in den niederlanden , die anhänger von le pens nationaler front in frankreich , sind beispiele für parteien oder bewegungen , die sich um das gemeinsame thema : ablehnung der zuwanderung gebildet haben und um forderung nach einer vereinfachten politik , um sie zu regeln .</seg>
-<seg grammar="grammar/grammar.out.3.gz" id="3">während individuen wie jörg haidar und jean @-@ marie le pen kommen und ( leider nicht zu bald ) wieder gehen mögen , wird die rassenfrage aus der europäischer politik nicht so bald verschwinden .</seg>
-<seg grammar="grammar/grammar.out.4.gz" id="4">eine alternde einheimische bevölkerung und immer offenere grenzen vermehren die rassistische zersplitterung in den europäischen ländern .</seg>
diff --git a/training/dtrain/examples/parallelized/work/shard.0.0.refs b/training/dtrain/examples/parallelized/work/shard.0.0.refs
deleted file mode 100644
index bef68fee..00000000
--- a/training/dtrain/examples/parallelized/work/shard.0.0.refs
+++ /dev/null
@@ -1,5 +0,0 @@
-europe 's divided racial house
-a common feature of europe 's extreme right is its racism and use of the immigration issue as a political wedge .
-the lega nord in italy , the vlaams blok in the netherlands , the supporters of le pen 's national front in france , are all examples of parties or movements formed on the common theme of aversion to immigrants and promotion of simplistic policies to control them .
-while individuals like jorg haidar and jean @-@ marie le pen may come and ( never to soon ) go , the race question will not disappear from european politics anytime soon .
-an aging population at home and ever more open borders imply increasing racial fragmentation in european countries .
diff --git a/training/dtrain/examples/parallelized/work/shard.1.0.in b/training/dtrain/examples/parallelized/work/shard.1.0.in
deleted file mode 100644
index b7695ce7..00000000
--- a/training/dtrain/examples/parallelized/work/shard.1.0.in
+++ /dev/null
@@ -1,5 +0,0 @@
-<seg grammar="grammar/grammar.out.5.gz" id="5">die großen parteien der rechten und der linken mitte haben sich dem problem gestellt , in dem sie den kopf in den sand gesteckt und allen aussichten zuwider gehofft haben , es möge bald verschwinden .</seg>
-<seg grammar="grammar/grammar.out.6.gz" id="6">das aber wird es nicht , wie die geschichte des rassismus in amerika deutlich zeigt .</seg>
-<seg grammar="grammar/grammar.out.7.gz" id="7">die beziehungen zwischen den rassen standen in den usa über jahrzehnte - und tun das noch heute - im zentrum der politischen debatte . das ging so weit , daß rassentrennung genauso wichtig wie das einkommen wurde , - wenn nicht sogar noch wichtiger - um politische zuneigungen und einstellungen zu bestimmen .</seg>
-<seg grammar="grammar/grammar.out.8.gz" id="8">der erste schritt , um mit der rassenfrage umzugehen ist , ursache und folgen rassistischer feindseligkeiten zu verstehen , auch dann , wenn das bedeutet , unangenehme tatsachen aufzudecken .</seg>
-<seg grammar="grammar/grammar.out.9.gz" id="9">genau das haben in den usa eine große anzahl an forschungsvorhaben in wirtschaft , soziologie , psychologie und politikwissenschaft geleistet . diese forschungen zeigten , daß menschen unterschiedlicher rasse einander deutlich weniger vertrauen .</seg>
diff --git a/training/dtrain/examples/parallelized/work/shard.1.0.refs b/training/dtrain/examples/parallelized/work/shard.1.0.refs
deleted file mode 100644
index 6076f6d5..00000000
--- a/training/dtrain/examples/parallelized/work/shard.1.0.refs
+++ /dev/null
@@ -1,5 +0,0 @@
-mainstream parties of the center left and center right have confronted this prospect by hiding their heads in the ground , hoping against hope that the problem will disappear .
-it will not , as america 's racial history clearly shows .
-race relations in the us have been for decades - and remain - at the center of political debate , to the point that racial cleavages are as important as income , if not more , as determinants of political preferences and attitudes .
-the first step to address racial politics is to understand the origin and consequences of racial animosity , even if it means uncovering unpleasant truths .
-this is precisely what a large amount of research in economics , sociology , psychology and political science has done for the us .
diff --git a/training/dtrain/examples/parallelized/work/weights.0 b/training/dtrain/examples/parallelized/work/weights.0
deleted file mode 100644
index ddd595a8..00000000
--- a/training/dtrain/examples/parallelized/work/weights.0
+++ /dev/null
@@ -1,12 +0,0 @@
-LanguageModel	0.7004298992212881
-PhraseModel_2	0.5576194336478857
-PhraseModel_1	0.41787318415343155
-PhraseModel_4	-0.46728502545635164
-PhraseModel_3	-0.029839521598455515
-Glue	-0.05760000000000068
-PhraseModel_6	-0.2716499999999978
-PhraseModel_0	-0.20831031065605327
-LanguageModel_OOV	-0.15205000000000077
-PassThrough	-0.1846500000000006
-WordPenalty	0.09636994553433414
-PhraseModel_5	-0.026900000000000257
diff --git a/training/dtrain/examples/parallelized/work/weights.0.0 b/training/dtrain/examples/parallelized/work/weights.0.0
deleted file mode 100644
index c9370b18..00000000
--- a/training/dtrain/examples/parallelized/work/weights.0.0
+++ /dev/null
@@ -1,12 +0,0 @@
-WordPenalty	-0.0079041595706392243
-LanguageModel	0.44781580828279532
-LanguageModel_OOV	-0.04010000000000042
-Glue	0.26629999999999948
-PhraseModel_0	-0.19299677809125185
-PhraseModel_1	0.71321026861732773
-PhraseModel_2	0.85195540993310537
-PhraseModel_3	-0.43986310822842656
-PhraseModel_4	-0.44802855630415955
-PhraseModel_5	-0.053800000000000514
-PhraseModel_6	-0.17879999999999835
-PassThrough	-0.14770000000000036
diff --git a/training/dtrain/examples/parallelized/work/weights.0.1 b/training/dtrain/examples/parallelized/work/weights.0.1
deleted file mode 100644
index 8fad3de8..00000000
--- a/training/dtrain/examples/parallelized/work/weights.0.1
+++ /dev/null
@@ -1,12 +0,0 @@
-WordPenalty	0.080605055841244472
-LanguageModel	-0.026571720531022844
-LanguageModel_OOV	-0.30024999999999141
-Glue	-0.26989999999999842
-PhraseModel_2	0.92000295209089566
-PhraseModel_1	0.67450748692470841
-PhraseModel_4	-0.5920000014976784
-PhraseModel_3	-0.36402437203127397
-PhraseModel_6	-0.28754999999999603
-PhraseModel_0	-0.32076244202907672
-PassThrough	-0.33284999999999004
-PhraseModel_5	-0.026900000000000257
diff --git a/training/dtrain/examples/parallelized/work/weights.1 b/training/dtrain/examples/parallelized/work/weights.1
deleted file mode 100644
index 03058a16..00000000
--- a/training/dtrain/examples/parallelized/work/weights.1
+++ /dev/null
@@ -1,12 +0,0 @@
-PhraseModel_2	0.8365578543552836
-PhraseModel_4	-0.5900840266009169
-PhraseModel_1	0.5312000609786991
-PhraseModel_0	-0.3872342271319619
-PhraseModel_3	-0.3728279676912084
-Glue	-0.2938500000000036
-PhraseModel_6	-0.2803499999999967
-PassThrough	-0.25014999999999626
-LanguageModel_OOV	-0.21754999999999702
-LanguageModel	0.07306061161169894
-WordPenalty	0.09576193325966899
-PhraseModel_5	-0.026900000000000257
diff --git a/training/dtrain/examples/parallelized/work/weights.1.0 b/training/dtrain/examples/parallelized/work/weights.1.0
deleted file mode 100644
index 6a6a65c1..00000000
--- a/training/dtrain/examples/parallelized/work/weights.1.0
+++ /dev/null
@@ -1,11 +0,0 @@
-WordPenalty	0.20064405063930751
-LanguageModel	0.9530439901597807
-LanguageModel_OOV	-0.26400000000000112
-Glue	-0.38150000000000084
-PhraseModel_0	-0.22362384322085468
-PhraseModel_1	0.12253609968953538
-PhraseModel_2	0.26328345736266612
-PhraseModel_3	0.38018406503151553
-PhraseModel_4	-0.48654149460854373
-PhraseModel_6	-0.36449999999999722
-PassThrough	-0.22160000000000085
diff --git a/training/dtrain/examples/parallelized/work/weights.1.1 b/training/dtrain/examples/parallelized/work/weights.1.1
deleted file mode 100644
index f56ea4a2..00000000
--- a/training/dtrain/examples/parallelized/work/weights.1.1
+++ /dev/null
@@ -1,12 +0,0 @@
-WordPenalty	0.1109188106780935
-LanguageModel	0.17269294375442074
-LanguageModel_OOV	-0.13485000000000266
-Glue	-0.3178000000000088
-PhraseModel_2	0.75311275661967159
-PhraseModel_1	0.38789263503268989
-PhraseModel_4	-0.58816805170415531
-PhraseModel_3	-0.38163156335114284
-PhraseModel_6	-0.27314999999999739
-PhraseModel_0	-0.45370601223484697
-PassThrough	-0.16745000000000249
-PhraseModel_5	-0.026900000000000257