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#!/bin/bash
# Adapted from https://github.com/facebookresearch/MIXER/blob/master/prepareData.sh
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=$SCRIPTS/tokenizer/tokenizer.perl
CLEAN=$SCRIPTS/training/clean-corpus-n.perl
NORM_PUNC=$SCRIPTS/tokenizer/normalize-punctuation.perl
REM_NON_PRINT_CHAR=$SCRIPTS/tokenizer/remove-non-printing-char.perl
BPEROOT=subword-nmt/subword_nmt
BPE_TOKENS=32000
URLS=(
"http://statmt.org/wmt13/training-parallel-europarl-v7.tgz"
"http://statmt.org/wmt13/training-parallel-commoncrawl.tgz"
"http://data.statmt.org/wmt18/translation-task/training-parallel-nc-v13.tgz"
"http://data.statmt.org/wmt18/translation-task/rapid2016.tgz"
"http://data.statmt.org/wmt17/translation-task/dev.tgz"
"http://statmt.org/wmt14/test-full.tgz"
)
FILES=(
"training-parallel-europarl-v7.tgz"
"training-parallel-commoncrawl.tgz"
"training-parallel-nc-v13.tgz"
"rapid2016.tgz"
"dev.tgz"
"test-full.tgz"
)
CORPORA=(
"training/europarl-v7.de-en"
"commoncrawl.de-en"
"training-parallel-nc-v13/news-commentary-v13.de-en"
"rapid2016.de-en"
)
if [ ! -d "$SCRIPTS" ]; then
echo "Please set SCRIPTS variable correctly to point to Moses scripts."
exit 1
fi
OUTDIR=wmt18_en_de
src=en
tgt=de
lang=en-de
prep=$OUTDIR
tmp=$prep/tmp
orig=orig
mkdir -p $orig $tmp $prep
cd $orig
for ((i=0;i<${#URLS[@]};++i)); do
file=${FILES[i]}
if [ -f $file ]; then
echo "$file already exists, skipping download"
else
url=${URLS[i]}
wget "$url"
if [ -f $file ]; then
echo "$url successfully downloaded."
else
echo "$url not successfully downloaded."
exit 1
fi
if [ ${file: -4} == ".tgz" ]; then
tar zxvf $file
elif [ ${file: -4} == ".tar" ]; then
tar xvf $file
fi
fi
done
cd ..
echo "pre-processing train data..."
for l in $src $tgt; do
rm $tmp/train.tags.$lang.tok.$l
for f in "${CORPORA[@]}"; do
cat $orig/$f.$l | \
perl $NORM_PUNC $l | \
perl $REM_NON_PRINT_CHAR | \
perl $TOKENIZER -threads 8 -a -l $l >> $tmp/train.tags.$lang.tok.$l
done
done
echo "pre-processing test data..."
for l in $src $tgt; do
if [ "$l" == "$src" ]; then
t="src"
else
t="ref"
fi
grep '<seg id' $orig/test-full/newstest2014-deen-$t.$l.sgm | \
sed -e 's/<seg id="[0-9]*">\s*//g' | \
sed -e 's/\s*<\/seg>\s*//g' | \
sed -e "s/\’/\'/g" | \
perl $TOKENIZER -threads 8 -a -l $l > $tmp/test.$l
echo ""
done
echo "splitting train and valid..."
for l in $src $tgt; do
awk '{if (NR%100 == 0) print $0; }' $tmp/train.tags.$lang.tok.$l > $tmp/valid.$l
awk '{if (NR%100 != 0) print $0; }' $tmp/train.tags.$lang.tok.$l > $tmp/train.$l
done
TRAIN=$tmp/train.de-en
BPE_CODE=$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 > $tmp/bpe.$f
done
done
perl $CLEAN -ratio 1.5 $tmp/bpe.train $src $tgt $prep/train 1 250
perl $CLEAN -ratio 1.5 $tmp/bpe.valid $src $tgt $prep/valid 1 250
for L in $src $tgt; do
cp $tmp/bpe.test.$L $prep/test.$L
done
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