DeepLearningExamples/PyTorch/Translation/GNMT/scripts/wmt16_en_de.sh
2020-08-01 15:47:34 +02:00

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#! /usr/bin/env bash
# Copyright 2017 Google Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# Copyright (c) 2018-2020, NVIDIA CORPORATION. All rights reserved.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
set -e
export LANG=C.UTF-8
export LC_ALL=C.UTF-8
OUTPUT_DIR=${1:-"data/wmt16_de_en"}
echo "Writing to ${OUTPUT_DIR}. To change this, set the OUTPUT_DIR environment variable."
OUTPUT_DIR_DATA="${OUTPUT_DIR}/data"
mkdir -p $OUTPUT_DIR_DATA
echo "Downloading Europarl v7. This may take a while..."
wget -nc -nv -O ${OUTPUT_DIR_DATA}/europarl-v7-de-en.tgz \
http://www.statmt.org/europarl/v7/de-en.tgz
echo "Downloading Common Crawl corpus. This may take a while..."
wget -nc -nv -O ${OUTPUT_DIR_DATA}/common-crawl.tgz \
http://www.statmt.org/wmt13/training-parallel-commoncrawl.tgz
echo "Downloading News Commentary v11. This may take a while..."
wget -nc -nv -O ${OUTPUT_DIR_DATA}/nc-v11.tgz \
http://data.statmt.org/wmt16/translation-task/training-parallel-nc-v11.tgz
echo "Downloading dev/test sets"
wget -nc -nv -O ${OUTPUT_DIR_DATA}/dev.tgz \
http://data.statmt.org/wmt16/translation-task/dev.tgz
wget -nc -nv -O ${OUTPUT_DIR_DATA}/test.tgz \
http://data.statmt.org/wmt16/translation-task/test.tgz
# Extract everything
echo "Extracting all files..."
mkdir -p "${OUTPUT_DIR_DATA}/europarl-v7-de-en"
tar -xvzf "${OUTPUT_DIR_DATA}/europarl-v7-de-en.tgz" -C "${OUTPUT_DIR_DATA}/europarl-v7-de-en"
mkdir -p "${OUTPUT_DIR_DATA}/common-crawl"
tar -xvzf "${OUTPUT_DIR_DATA}/common-crawl.tgz" -C "${OUTPUT_DIR_DATA}/common-crawl"
mkdir -p "${OUTPUT_DIR_DATA}/nc-v11"
tar -xvzf "${OUTPUT_DIR_DATA}/nc-v11.tgz" -C "${OUTPUT_DIR_DATA}/nc-v11"
mkdir -p "${OUTPUT_DIR_DATA}/dev"
tar -xvzf "${OUTPUT_DIR_DATA}/dev.tgz" -C "${OUTPUT_DIR_DATA}/dev"
mkdir -p "${OUTPUT_DIR_DATA}/test"
tar -xvzf "${OUTPUT_DIR_DATA}/test.tgz" -C "${OUTPUT_DIR_DATA}/test"
# Concatenate Training data
cat "${OUTPUT_DIR_DATA}/europarl-v7-de-en/europarl-v7.de-en.en" \
"${OUTPUT_DIR_DATA}/common-crawl/commoncrawl.de-en.en" \
"${OUTPUT_DIR_DATA}/nc-v11/training-parallel-nc-v11/news-commentary-v11.de-en.en" \
> "${OUTPUT_DIR}/train.en"
wc -l "${OUTPUT_DIR}/train.en"
cat "${OUTPUT_DIR_DATA}/europarl-v7-de-en/europarl-v7.de-en.de" \
"${OUTPUT_DIR_DATA}/common-crawl/commoncrawl.de-en.de" \
"${OUTPUT_DIR_DATA}/nc-v11/training-parallel-nc-v11/news-commentary-v11.de-en.de" \
> "${OUTPUT_DIR}/train.de"
wc -l "${OUTPUT_DIR}/train.de"
# Clone Moses
if [ ! -d "${OUTPUT_DIR}/mosesdecoder" ]; then
echo "Cloning moses for data processing"
git clone https://github.com/moses-smt/mosesdecoder.git "${OUTPUT_DIR}/mosesdecoder"
cd ${OUTPUT_DIR}/mosesdecoder
git reset --hard 8c5eaa1a122236bbf927bde4ec610906fea599e6
cd -
fi
# Convert SGM files
# Convert newstest2014 data into raw text format
${OUTPUT_DIR}/mosesdecoder/scripts/ems/support/input-from-sgm.perl \
< ${OUTPUT_DIR_DATA}/dev/dev/newstest2014-deen-src.de.sgm \
> ${OUTPUT_DIR_DATA}/dev/dev/newstest2014.de
${OUTPUT_DIR}/mosesdecoder/scripts/ems/support/input-from-sgm.perl \
< ${OUTPUT_DIR_DATA}/dev/dev/newstest2014-deen-ref.en.sgm \
> ${OUTPUT_DIR_DATA}/dev/dev/newstest2014.en
# Convert newstest2015 data into raw text format
${OUTPUT_DIR}/mosesdecoder/scripts/ems/support/input-from-sgm.perl \
< ${OUTPUT_DIR_DATA}/dev/dev/newstest2015-deen-src.de.sgm \
> ${OUTPUT_DIR_DATA}/dev/dev/newstest2015.de
${OUTPUT_DIR}/mosesdecoder/scripts/ems/support/input-from-sgm.perl \
< ${OUTPUT_DIR_DATA}/dev/dev/newstest2015-deen-ref.en.sgm \
> ${OUTPUT_DIR_DATA}/dev/dev/newstest2015.en
# Convert newstest2016 data into raw text format
${OUTPUT_DIR}/mosesdecoder/scripts/ems/support/input-from-sgm.perl \
< ${OUTPUT_DIR_DATA}/test/test/newstest2016-deen-src.de.sgm \
> ${OUTPUT_DIR_DATA}/test/test/newstest2016.de
${OUTPUT_DIR}/mosesdecoder/scripts/ems/support/input-from-sgm.perl \
< ${OUTPUT_DIR_DATA}/test/test/newstest2016-deen-ref.en.sgm \
> ${OUTPUT_DIR_DATA}/test/test/newstest2016.en
# Copy dev/test data to output dir
cp ${OUTPUT_DIR_DATA}/dev/dev/newstest20*.de ${OUTPUT_DIR}
cp ${OUTPUT_DIR_DATA}/dev/dev/newstest20*.en ${OUTPUT_DIR}
cp ${OUTPUT_DIR_DATA}/test/test/newstest20*.de ${OUTPUT_DIR}
cp ${OUTPUT_DIR_DATA}/test/test/newstest20*.en ${OUTPUT_DIR}
# Tokenize data
for f in ${OUTPUT_DIR}/*.de; do
echo "Tokenizing $f..."
${OUTPUT_DIR}/mosesdecoder/scripts/tokenizer/tokenizer.perl -q -l de -threads 8 < $f > ${f%.*}.tok.de
done
for f in ${OUTPUT_DIR}/*.en; do
echo "Tokenizing $f..."
${OUTPUT_DIR}/mosesdecoder/scripts/tokenizer/tokenizer.perl -q -l en -threads 8 < $f > ${f%.*}.tok.en
done
# Clean all corpora
for f in ${OUTPUT_DIR}/*.en; do
fbase=${f%.*}
echo "Cleaning ${fbase}..."
${OUTPUT_DIR}/mosesdecoder/scripts/training/clean-corpus-n.perl $fbase de en "${fbase}.clean" 1 80
done
# Create dev dataset
cat "${OUTPUT_DIR}/newstest2015.tok.clean.en" \
"${OUTPUT_DIR}/newstest2016.tok.clean.en" \
> "${OUTPUT_DIR}/newstest_dev.tok.clean.en"
cat "${OUTPUT_DIR}/newstest2015.tok.clean.de" \
"${OUTPUT_DIR}/newstest2016.tok.clean.de" \
> "${OUTPUT_DIR}/newstest_dev.tok.clean.de"
# Filter datasets
python3 scripts/filter_dataset.py \
-f1 ${OUTPUT_DIR}/train.tok.clean.en \
-f2 ${OUTPUT_DIR}/train.tok.clean.de
python3 scripts/filter_dataset.py \
-f1 ${OUTPUT_DIR}/newstest_dev.tok.clean.en \
-f2 ${OUTPUT_DIR}/newstest_dev.tok.clean.de
# Generate Subword Units (BPE)
# Learn Shared BPE
for merge_ops in 32000; do
echo "Learning BPE with merge_ops=${merge_ops}. This may take a while..."
cat "${OUTPUT_DIR}/train.tok.clean.de" "${OUTPUT_DIR}/train.tok.clean.en" | \
subword-nmt learn-bpe -s $merge_ops > "${OUTPUT_DIR}/bpe.${merge_ops}"
echo "Apply BPE with merge_ops=${merge_ops} to tokenized files..."
for lang in en de; do
for f in ${OUTPUT_DIR}/*.tok.${lang} ${OUTPUT_DIR}/*.tok.clean.${lang}; do
outfile="${f%.*}.bpe.${merge_ops}.${lang}"
subword-nmt apply-bpe -c "${OUTPUT_DIR}/bpe.${merge_ops}" < $f > "${outfile}"
echo ${outfile}
done
done
# Create vocabulary file for BPE
cat "${OUTPUT_DIR}/train.tok.clean.bpe.${merge_ops}.en" "${OUTPUT_DIR}/train.tok.clean.bpe.${merge_ops}.de" | \
subword-nmt get-vocab | cut -f1 -d ' ' > "${OUTPUT_DIR}/vocab.bpe.${merge_ops}"
done
echo "All done."