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-rw-r--r--training/dtrain/examples/parallelized/README5
-rw-r--r--training/dtrain/examples/parallelized/cdec.ini22
-rw-r--r--training/dtrain/examples/parallelized/dtrain.ini14
-rw-r--r--training/dtrain/examples/parallelized/grammar/grammar.out.0.gzbin8318 -> 0 bytes
-rw-r--r--training/dtrain/examples/parallelized/grammar/grammar.out.1.gzbin358560 -> 0 bytes
-rw-r--r--training/dtrain/examples/parallelized/grammar/grammar.out.2.gzbin1014466 -> 0 bytes
-rw-r--r--training/dtrain/examples/parallelized/grammar/grammar.out.3.gzbin391811 -> 0 bytes
-rw-r--r--training/dtrain/examples/parallelized/grammar/grammar.out.4.gzbin149590 -> 0 bytes
-rw-r--r--training/dtrain/examples/parallelized/grammar/grammar.out.5.gzbin537024 -> 0 bytes
-rw-r--r--training/dtrain/examples/parallelized/grammar/grammar.out.6.gzbin291286 -> 0 bytes
-rw-r--r--training/dtrain/examples/parallelized/grammar/grammar.out.7.gzbin1038140 -> 0 bytes
-rw-r--r--training/dtrain/examples/parallelized/grammar/grammar.out.8.gzbin419889 -> 0 bytes
-rw-r--r--training/dtrain/examples/parallelized/grammar/grammar.out.9.gzbin409140 -> 0 bytes
-rw-r--r--training/dtrain/examples/parallelized/in10
-rw-r--r--training/dtrain/examples/parallelized/refs10
-rw-r--r--training/dtrain/examples/parallelized/work/out.0.062
-rw-r--r--training/dtrain/examples/parallelized/work/out.0.163
-rw-r--r--training/dtrain/examples/parallelized/work/out.1.062
-rw-r--r--training/dtrain/examples/parallelized/work/out.1.163
-rw-r--r--training/dtrain/examples/parallelized/work/shard.0.0.in5
-rw-r--r--training/dtrain/examples/parallelized/work/shard.0.0.refs5
-rw-r--r--training/dtrain/examples/parallelized/work/shard.1.0.in5
-rw-r--r--training/dtrain/examples/parallelized/work/shard.1.0.refs5
-rw-r--r--training/dtrain/examples/parallelized/work/weights.012
-rw-r--r--training/dtrain/examples/parallelized/work/weights.0.012
-rw-r--r--training/dtrain/examples/parallelized/work/weights.0.112
-rw-r--r--training/dtrain/examples/parallelized/work/weights.112
-rw-r--r--training/dtrain/examples/parallelized/work/weights.1.011
-rw-r--r--training/dtrain/examples/parallelized/work/weights.1.112
29 files changed, 0 insertions, 402 deletions
diff --git a/training/dtrain/examples/parallelized/README b/training/dtrain/examples/parallelized/README
deleted file mode 100644
index 89715105..00000000
--- a/training/dtrain/examples/parallelized/README
+++ /dev/null
@@ -1,5 +0,0 @@
-run for example
- ../../parallelize.rb ./dtrain.ini 4 false 2 2 ./in ./refs
-
-final weights will be in the file work/weights.3
-
diff --git a/training/dtrain/examples/parallelized/cdec.ini b/training/dtrain/examples/parallelized/cdec.ini
deleted file mode 100644
index 5773029a..00000000
--- a/training/dtrain/examples/parallelized/cdec.ini
+++ /dev/null
@@ -1,22 +0,0 @@
-formalism=scfg
-add_pass_through_rules=true
-intersection_strategy=cube_pruning
-cubepruning_pop_limit=200
-scfg_max_span_limit=15
-feature_function=WordPenalty
-feature_function=KLanguageModel ../standard//nc-wmt11.en.srilm.gz
-#feature_function=ArityPenalty
-#feature_function=CMR2008ReorderingFeatures
-#feature_function=Dwarf
-#feature_function=InputIndicator
-#feature_function=LexNullJump
-#feature_function=NewJump
-#feature_function=NgramFeatures
-#feature_function=NonLatinCount
-#feature_function=OutputIndicator
-#feature_function=RuleIdentityFeatures
-#feature_function=RuleNgramFeatures
-#feature_function=RuleShape
-#feature_function=SourceSpanSizeFeatures
-#feature_function=SourceWordPenalty
-#feature_function=SpanFeatures
diff --git a/training/dtrain/examples/parallelized/dtrain.ini b/training/dtrain/examples/parallelized/dtrain.ini
deleted file mode 100644
index 0b0932d6..00000000
--- a/training/dtrain/examples/parallelized/dtrain.ini
+++ /dev/null
@@ -1,14 +0,0 @@
-k=100
-N=4
-learning_rate=0.0001
-gamma=0
-loss_margin=1.0
-epochs=1
-scorer=stupid_bleu
-sample_from=kbest
-filter=uniq
-pair_sampling=XYX
-hi_lo=0.1
-select_weights=last
-print_weights=Glue WordPenalty LanguageModel LanguageModel_OOV PhraseModel_0 PhraseModel_1 PhraseModel_2 PhraseModel_3 PhraseModel_4 PhraseModel_5 PhraseModel_6 PassThrough
-decoder_config=cdec.ini
diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.0.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.0.gz
deleted file mode 100644
index 1e28a24b..00000000
--- a/training/dtrain/examples/parallelized/grammar/grammar.out.0.gz
+++ /dev/null
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diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.1.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.1.gz
deleted file mode 100644
index 372f5675..00000000
--- a/training/dtrain/examples/parallelized/grammar/grammar.out.1.gz
+++ /dev/null
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diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.2.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.2.gz
deleted file mode 100644
index 145d0dc0..00000000
--- a/training/dtrain/examples/parallelized/grammar/grammar.out.2.gz
+++ /dev/null
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diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.3.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.3.gz
deleted file mode 100644
index 105593ff..00000000
--- a/training/dtrain/examples/parallelized/grammar/grammar.out.3.gz
+++ /dev/null
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diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.4.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.4.gz
deleted file mode 100644
index 30781f48..00000000
--- a/training/dtrain/examples/parallelized/grammar/grammar.out.4.gz
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diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.5.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.5.gz
deleted file mode 100644
index 834ee759..00000000
--- a/training/dtrain/examples/parallelized/grammar/grammar.out.5.gz
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diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.6.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.6.gz
deleted file mode 100644
index 2e76f348..00000000
--- a/training/dtrain/examples/parallelized/grammar/grammar.out.6.gz
+++ /dev/null
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diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.7.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.7.gz
deleted file mode 100644
index 3741a887..00000000
--- a/training/dtrain/examples/parallelized/grammar/grammar.out.7.gz
+++ /dev/null
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diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.8.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.8.gz
deleted file mode 100644
index ebf6bd0c..00000000
--- a/training/dtrain/examples/parallelized/grammar/grammar.out.8.gz
+++ /dev/null
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diff --git a/training/dtrain/examples/parallelized/grammar/grammar.out.9.gz b/training/dtrain/examples/parallelized/grammar/grammar.out.9.gz
deleted file mode 100644
index c1791059..00000000
--- a/training/dtrain/examples/parallelized/grammar/grammar.out.9.gz
+++ /dev/null
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diff --git a/training/dtrain/examples/parallelized/in b/training/dtrain/examples/parallelized/in
deleted file mode 100644
index 51d01fe7..00000000
--- a/training/dtrain/examples/parallelized/in
+++ /dev/null
@@ -1,10 +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>
-<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/refs b/training/dtrain/examples/parallelized/refs
deleted file mode 100644
index 632e27b0..00000000
--- a/training/dtrain/examples/parallelized/refs
+++ /dev/null
@@ -1,10 +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 .
-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/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
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deleted file mode 100644
index c9370b18..00000000
--- a/training/dtrain/examples/parallelized/work/weights.0.0
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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
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deleted file mode 100644
index 03058a16..00000000
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deleted file mode 100644
index 6a6a65c1..00000000
--- a/training/dtrain/examples/parallelized/work/weights.1.0
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deleted file mode 100644
index f56ea4a2..00000000
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