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-rw-r--r--training/dtrain/test/example/README8
-rw-r--r--training/dtrain/test/example/cdec.ini25
-rw-r--r--training/dtrain/test/example/dtrain.ini22
-rw-r--r--training/dtrain/test/example/expected-output89
4 files changed, 0 insertions, 144 deletions
diff --git a/training/dtrain/test/example/README b/training/dtrain/test/example/README
deleted file mode 100644
index 6937b11b..00000000
--- a/training/dtrain/test/example/README
+++ /dev/null
@@ -1,8 +0,0 @@
-Small example of input format for distributed training.
-Call dtrain from cdec/dtrain/ with ./dtrain -c test/example/dtrain.ini .
-
-For this to work, undef 'DTRAIN_LOCAL' in dtrain.h
-and recompile.
-
-Data is here: http://simianer.de/#dtrain
-
diff --git a/training/dtrain/test/example/cdec.ini b/training/dtrain/test/example/cdec.ini
deleted file mode 100644
index d5955f0e..00000000
--- a/training/dtrain/test/example/cdec.ini
+++ /dev/null
@@ -1,25 +0,0 @@
-formalism=scfg
-add_pass_through_rules=true
-scfg_max_span_limit=15
-intersection_strategy=cube_pruning
-cubepruning_pop_limit=30
-feature_function=WordPenalty
-feature_function=KLanguageModel test/example/nc-wmt11.en.srilm.gz
-# all currently working feature functions for translation:
-# (with those features active that were used in the ACL paper)
-#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=RuleSourceBigramFeatures
-feature_function=RuleTargetBigramFeatures
-feature_function=RuleShape
-#feature_function=SourceSpanSizeFeatures
-#feature_function=SourceWordPenalty
-#feature_function=SpanFeatures
diff --git a/training/dtrain/test/example/dtrain.ini b/training/dtrain/test/example/dtrain.ini
deleted file mode 100644
index 72d50ca1..00000000
--- a/training/dtrain/test/example/dtrain.ini
+++ /dev/null
@@ -1,22 +0,0 @@
-input=test/example/nc-wmt11.1k.gz # use '-' for STDIN
-output=- # a weights file (add .gz for gzip compression) or STDOUT '-'
-select_weights=VOID # don't output weights
-decoder_config=test/example/cdec.ini # config for cdec
-# weights for these features will be printed on each iteration
-print_weights=Glue WordPenalty LanguageModel LanguageModel_OOV PhraseModel_0 PhraseModel_1 PhraseModel_2 PhraseModel_3 PhraseModel_4 PhraseModel_5 PhraseModel_6 PassThrough
-tmp=/tmp
-stop_after=10 # stop epoch after 10 inputs
-
-# interesting stuff
-epochs=2 # run over input 2 times
-k=100 # use 100best lists
-N=4 # optimize (approx) BLEU4
-scorer=stupid_bleu # use 'stupid' BLEU+1
-learning_rate=1.0 # learning rate, don't care if gamma=0 (perceptron)
-gamma=0 # use SVM reg
-sample_from=kbest # use kbest lists (as opposed to forest)
-filter=uniq # only unique entries in kbest (surface form)
-pair_sampling=XYX
-hi_lo=0.1 # 10 vs 80 vs 10 and 80 vs 10 here
-pair_threshold=0 # minimum distance in BLEU (this will still only use pairs with diff > 0)
-loss_margin=0
diff --git a/training/dtrain/test/example/expected-output b/training/dtrain/test/example/expected-output
deleted file mode 100644
index 05326763..00000000
--- a/training/dtrain/test/example/expected-output
+++ /dev/null
@@ -1,89 +0,0 @@
- cdec cfg 'test/example/cdec.ini'
-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
-****************************************************************************************************
- Example feature: Shape_S00000_T00000
-Seeding random number sequence to 2912000813
-
-dtrain
-Parameters:
- k 100
- N 4
- T 2
- scorer 'stupid_bleu'
- sample from 'kbest'
- filter 'uniq'
- learning rate 1
- gamma 0
- loss margin 0
- pairs 'XYX'
- hi lo 0.1
- pair threshold 0
- select weights 'VOID'
- l1 reg 0 'none'
- max pairs 4294967295
- cdec cfg 'test/example/cdec.ini'
- input 'test/example/nc-wmt11.1k.gz'
- output '-'
- stop_after 10
-(a dot represents 10 inputs)
-Iteration #1 of 2.
- . 10
-Stopping after 10 input sentences.
-WEIGHTS
- Glue = -637
- WordPenalty = +1064
- LanguageModel = +1175.3
- LanguageModel_OOV = -1437
- PhraseModel_0 = +1935.6
- PhraseModel_1 = +2499.3
- PhraseModel_2 = +964.96
- PhraseModel_3 = +1410.8
- PhraseModel_4 = -5977.9
- PhraseModel_5 = +522
- PhraseModel_6 = +1089
- PassThrough = -1308
- ---
- 1best avg score: 0.16963 (+0.16963)
- 1best avg model score: 64485 (+64485)
- avg # pairs: 1494.4
- avg # rank err: 702.6
- avg # margin viol: 0
- non0 feature count: 528
- avg list sz: 85.7
- avg f count: 102.75
-(time 0.083 min, 0.5 s/S)
-
-Iteration #2 of 2.
- . 10
-WEIGHTS
- Glue = -1196
- WordPenalty = +809.52
- LanguageModel = +3112.1
- LanguageModel_OOV = -1464
- PhraseModel_0 = +3895.5
- PhraseModel_1 = +4683.4
- PhraseModel_2 = +1092.8
- PhraseModel_3 = +1079.6
- PhraseModel_4 = -6827.7
- PhraseModel_5 = -888
- PhraseModel_6 = +142
- PassThrough = -1335
- ---
- 1best avg score: 0.277 (+0.10736)
- 1best avg model score: -3110.5 (-67595)
- avg # pairs: 1144.2
- avg # rank err: 529.1
- avg # margin viol: 0
- non0 feature count: 859
- avg list sz: 74.9
- avg f count: 112.84
-(time 0.067 min, 0.4 s/S)
-
-Writing weights file to '-' ...
-done
-
----
-Best iteration: 2 [SCORE 'stupid_bleu'=0.277].
-This took 0.15 min.