diff options
Diffstat (limited to 'dtrain/test')
| -rw-r--r-- | dtrain/test/example/README | 4 | ||||
| -rw-r--r-- | dtrain/test/example/dtrain.ini | 3 | ||||
| -rw-r--r-- | dtrain/test/example/expected-output | 125 |
3 files changed, 129 insertions, 3 deletions
diff --git a/dtrain/test/example/README b/dtrain/test/example/README index b3ea5f06..6937b11b 100644 --- a/dtrain/test/example/README +++ b/dtrain/test/example/README @@ -1,8 +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, disable '#define DTRAIN_LOCAL' from dtrain.h +For this to work, undef 'DTRAIN_LOCAL' in dtrain.h and recompile. -Data is here: http://simianer.de/dtrain +Data is here: http://simianer.de/#dtrain diff --git a/dtrain/test/example/dtrain.ini b/dtrain/test/example/dtrain.ini index f87ee9cf..c8ac7c3f 100644 --- a/dtrain/test/example/dtrain.ini +++ b/dtrain/test/example/dtrain.ini @@ -5,7 +5,7 @@ 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 20 inputs +stop_after=10 # stop epoch after 10 inputs # interesting stuff epochs=3 # run over input 3 times @@ -19,3 +19,4 @@ 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 new file mode 100644 index 00000000..25d2c069 --- /dev/null +++ b/dtrain/test/example/expected-output @@ -0,0 +1,125 @@ + cdec cfg 'test/example/cdec.ini' +feature: WordPenalty (no config parameters) +State is 0 bytes for feature WordPenalty +feature: KLanguageModel (with config parameters 'test/example/nc-wmt11.en.srilm.gz') +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 +**************************************************************************************************** +Loaded 5-gram KLM from test/example/nc-wmt11.en.srilm.gz (MapSize=49581) +State is 98 bytes for feature KLanguageModel test/example/nc-wmt11.en.srilm.gz +feature: RuleIdentityFeatures (no config parameters) +State is 0 bytes for feature RuleIdentityFeatures +feature: RuleNgramFeatures (no config parameters) +State is 0 bytes for feature RuleNgramFeatures +feature: RuleShape (no config parameters) + Example feature: Shape_S00000_T00000 +State is 0 bytes for feature RuleShape +Seeding random number sequence to 1072059181 + +dtrain +Parameters: + k 100 + N 4 + T 3 + scorer 'stupid_bleu' + sample from 'kbest' + filter 'uniq' + learning rate 0.0001 + gamma 0 + loss margin 0 + pairs 'XYX' + hi lo 0.1 + pair threshold 0 + select weights 'VOID' + l1 reg 0 'none' + 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 3. + . 10 +Stopping after 10 input sentences. +WEIGHTS + Glue = -0.0293 + WordPenalty = +0.049075 + LanguageModel = +0.24345 + LanguageModel_OOV = -0.2029 + PhraseModel_0 = +0.0084102 + PhraseModel_1 = +0.021729 + PhraseModel_2 = +0.014922 + PhraseModel_3 = +0.104 + PhraseModel_4 = -0.14308 + PhraseModel_5 = +0.0247 + PhraseModel_6 = -0.012 + PassThrough = -0.2161 + --- + 1best avg score: 0.16872 (+0.16872) + 1best avg model score: -1.8276 (-1.8276) + avg # pairs: 1121.1 + avg # rank err: 555.6 + avg # margin viol: 0 + non0 feature count: 277 + avg list sz: 77.2 + avg f count: 90.96 +(time 0.1 min, 0.6 s/S) + +Iteration #2 of 3. + . 10 +WEIGHTS + Glue = -0.3526 + WordPenalty = +0.067576 + LanguageModel = +1.155 + LanguageModel_OOV = -0.2728 + PhraseModel_0 = -0.025529 + PhraseModel_1 = +0.095869 + PhraseModel_2 = +0.094567 + PhraseModel_3 = +0.12482 + PhraseModel_4 = -0.36533 + PhraseModel_5 = +0.1068 + PhraseModel_6 = -0.1517 + PassThrough = -0.286 + --- + 1best avg score: 0.18394 (+0.015221) + 1best avg model score: 3.205 (+5.0326) + avg # pairs: 1168.3 + avg # rank err: 594.8 + avg # margin viol: 0 + non0 feature count: 543 + avg list sz: 77.5 + avg f count: 85.916 +(time 0.083 min, 0.5 s/S) + +Iteration #3 of 3. + . 10 +WEIGHTS + Glue = -0.392 + WordPenalty = +0.071963 + LanguageModel = +0.81266 + LanguageModel_OOV = -0.4177 + PhraseModel_0 = -0.2649 + PhraseModel_1 = -0.17931 + PhraseModel_2 = +0.038261 + PhraseModel_3 = +0.20261 + PhraseModel_4 = -0.42621 + PhraseModel_5 = +0.3198 + PhraseModel_6 = -0.1437 + PassThrough = -0.4309 + --- + 1best avg score: 0.2962 (+0.11225) + 1best avg model score: -36.274 (-39.479) + avg # pairs: 1109.6 + avg # rank err: 515.9 + avg # margin viol: 0 + non0 feature count: 741 + avg list sz: 77 + avg f count: 88.982 +(time 0.083 min, 0.5 s/S) + +Writing weights file to '-' ... +done + +--- +Best iteration: 3 [SCORE 'stupid_bleu'=0.2962]. +This took 0.26667 min. |