Loading README.md +1 −1 Changes for README.md: 1 added line, 1 removed line. Original line number Diff line number Diff line Loading @@ -108,7 +108,7 @@ $ cd .. $ TEXT=data/iwslt14.tokenized.de-en $ python preprocess.py --source-lang de --target-lang en \ --trainpref $TEXT/train --validpref $TEXT/valid --testpref $TEXT/test \ --thresholdtgt 3 --thresholdsrc 3 --destdir data-bin/iwslt14.tokenized.de-en --destdir data-bin/iwslt14.tokenized.de-en ``` This will write binarized data that can be used for model training to `data-bin/iwslt14.tokenized.de-en`. Loading data/prepare-iwslt14.sh +25 −3 Changes for data/prepare-iwslt14.sh: 25 added lines, 3 removed lines. Original line number Diff line number Diff line Loading @@ -5,10 +5,15 @@ echo 'Cloning Moses github repository (for tokenization scripts)...' git clone https://github.com/moses-smt/mosesdecoder.git echo 'Cloning Subword NMT repository (for BPE pre-processing)...' git clone https://github.com/rsennrich/subword-nmt.git SCRIPTS=mosesdecoder/scripts TOKENIZER=$SCRIPTS/tokenizer/tokenizer.perl LC=$SCRIPTS/tokenizer/lowercase.perl CLEAN=$SCRIPTS/training/clean-corpus-n.perl BPEROOT=subword-nmt BPE_TOKENS=10000 URL="https://wit3.fbk.eu/archive/2014-01/texts/de/en/de-en.tgz" GZ=de-en.tgz Loading Loading @@ -81,13 +86,30 @@ done echo "creating train, valid, test..." for l in $src $tgt; do awk '{if (NR%23 == 0) print $0; }' $tmp/train.tags.de-en.$l > $prep/valid.$l awk '{if (NR%23 != 0) print $0; }' $tmp/train.tags.de-en.$l > $prep/train.$l awk '{if (NR%23 == 0) print $0; }' $tmp/train.tags.de-en.$l > $tmp/valid.$l awk '{if (NR%23 != 0) print $0; }' $tmp/train.tags.de-en.$l > $tmp/train.$l cat $tmp/IWSLT14.TED.dev2010.de-en.$l \ $tmp/IWSLT14.TEDX.dev2012.de-en.$l \ $tmp/IWSLT14.TED.tst2010.de-en.$l \ $tmp/IWSLT14.TED.tst2011.de-en.$l \ $tmp/IWSLT14.TED.tst2012.de-en.$l \ > $prep/test.$l > $tmp/test.$l done TRAIN=$tmp/train.en-de BPE_CODE=$prep/code rm -f $TRAIN for l in $src $tgt; do cat $tmp/train.$l >> $TRAIN done echo "learn_bpe.py on ${TRAIN}..." python $BPEROOT/learn_bpe.py -s $BPE_TOKENS < $TRAIN > $BPE_CODE for L in $src $tgt; do for f in train.$L valid.$L test.$L; do echo "apply_bpe.py to ${f}..." python $BPEROOT/apply_bpe.py -c $BPE_CODE < $tmp/$f > $prep/$f done done Loading
README.md +1 −1 Changes for README.md: 1 added line, 1 removed line. Original line number Diff line number Diff line Loading @@ -108,7 +108,7 @@ $ cd .. $ TEXT=data/iwslt14.tokenized.de-en $ python preprocess.py --source-lang de --target-lang en \ --trainpref $TEXT/train --validpref $TEXT/valid --testpref $TEXT/test \ --thresholdtgt 3 --thresholdsrc 3 --destdir data-bin/iwslt14.tokenized.de-en --destdir data-bin/iwslt14.tokenized.de-en ``` This will write binarized data that can be used for model training to `data-bin/iwslt14.tokenized.de-en`. Loading
data/prepare-iwslt14.sh +25 −3 Changes for data/prepare-iwslt14.sh: 25 added lines, 3 removed lines. Original line number Diff line number Diff line Loading @@ -5,10 +5,15 @@ echo 'Cloning Moses github repository (for tokenization scripts)...' git clone https://github.com/moses-smt/mosesdecoder.git echo 'Cloning Subword NMT repository (for BPE pre-processing)...' git clone https://github.com/rsennrich/subword-nmt.git SCRIPTS=mosesdecoder/scripts TOKENIZER=$SCRIPTS/tokenizer/tokenizer.perl LC=$SCRIPTS/tokenizer/lowercase.perl CLEAN=$SCRIPTS/training/clean-corpus-n.perl BPEROOT=subword-nmt BPE_TOKENS=10000 URL="https://wit3.fbk.eu/archive/2014-01/texts/de/en/de-en.tgz" GZ=de-en.tgz Loading Loading @@ -81,13 +86,30 @@ done echo "creating train, valid, test..." for l in $src $tgt; do awk '{if (NR%23 == 0) print $0; }' $tmp/train.tags.de-en.$l > $prep/valid.$l awk '{if (NR%23 != 0) print $0; }' $tmp/train.tags.de-en.$l > $prep/train.$l awk '{if (NR%23 == 0) print $0; }' $tmp/train.tags.de-en.$l > $tmp/valid.$l awk '{if (NR%23 != 0) print $0; }' $tmp/train.tags.de-en.$l > $tmp/train.$l cat $tmp/IWSLT14.TED.dev2010.de-en.$l \ $tmp/IWSLT14.TEDX.dev2012.de-en.$l \ $tmp/IWSLT14.TED.tst2010.de-en.$l \ $tmp/IWSLT14.TED.tst2011.de-en.$l \ $tmp/IWSLT14.TED.tst2012.de-en.$l \ > $prep/test.$l > $tmp/test.$l done TRAIN=$tmp/train.en-de BPE_CODE=$prep/code rm -f $TRAIN for l in $src $tgt; do cat $tmp/train.$l >> $TRAIN done echo "learn_bpe.py on ${TRAIN}..." python $BPEROOT/learn_bpe.py -s $BPE_TOKENS < $TRAIN > $BPE_CODE for L in $src $tgt; do for f in train.$L valid.$L test.$L; do echo "apply_bpe.py to ${f}..." python $BPEROOT/apply_bpe.py -c $BPE_CODE < $tmp/$f > $prep/$f done done