From 1b8181bf0d6e9137e6b9ccdbe414aec37377a1a9 Mon Sep 17 00:00:00 2001 From: Chris Dyer Date: Sun, 18 Nov 2012 13:35:42 -0500 Subject: major restructure of the training code --- training/dtrain/test/example/README | 8 +++ training/dtrain/test/example/cdec.ini | 25 ++++++++ training/dtrain/test/example/dtrain.ini | 22 +++++++ training/dtrain/test/example/expected-output | 89 ++++++++++++++++++++++++++++ 4 files changed, 144 insertions(+) create mode 100644 training/dtrain/test/example/README create mode 100644 training/dtrain/test/example/cdec.ini create mode 100644 training/dtrain/test/example/dtrain.ini create mode 100644 training/dtrain/test/example/expected-output (limited to 'training/dtrain/test/example') diff --git a/training/dtrain/test/example/README b/training/dtrain/test/example/README new file mode 100644 index 00000000..6937b11b --- /dev/null +++ b/training/dtrain/test/example/README @@ -0,0 +1,8 @@ +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 new file mode 100644 index 00000000..d5955f0e --- /dev/null +++ b/training/dtrain/test/example/cdec.ini @@ -0,0 +1,25 @@ +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 new file mode 100644 index 00000000..72d50ca1 --- /dev/null +++ b/training/dtrain/test/example/dtrain.ini @@ -0,0 +1,22 @@ +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 new file mode 100644 index 00000000..05326763 --- /dev/null +++ b/training/dtrain/test/example/expected-output @@ -0,0 +1,89 @@ + 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. -- cgit v1.2.3