major restructure of the training code

4 files changed, 0 insertions, 144 deletions

diff --git a/dtrain/test/example/README b/dtrain/test/example/README
deleted file mode 100644
index 6937b11b..00000000
--- a/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/dtrain/test/example/cdec.ini b/dtrain/test/example/cdec.ini
deleted file mode 100644
index d5955f0e..00000000
--- a/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/dtrain/test/example/dtrain.ini b/dtrain/test/example/dtrain.ini
deleted file mode 100644
index 72d50ca1..00000000
--- a/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/dtrain/test/example/expected-output b/dtrain/test/example/expected-output
deleted file mode 100644
index 05326763..00000000
--- a/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.