From 3b5629c0c5cfdc5e43bf8bd12e4f72b9a500021d Mon Sep 17 00:00:00 2001 From: "NAUSICAA\\Julian" Date: Tue, 20 Nov 2018 00:46:04 -0300 Subject: [PATCH] Removing files --- prepare_cls.sh | 15 ------------ prepare_rcv.sh | 50 --------------------------------------- ulmfit/merge_langs.py | 35 --------------------------- ulmfit/postprocess_cls.py | 23 ------------------ ulmfit/postprocess_rcv.py | 12 ---------- 5 files changed, 135 deletions(-) delete mode 100644 prepare_cls.sh delete mode 100644 prepare_rcv.sh delete mode 100644 ulmfit/merge_langs.py delete mode 100644 ulmfit/postprocess_cls.py delete mode 100644 ulmfit/postprocess_rcv.py diff --git a/prepare_cls.sh b/prepare_cls.sh deleted file mode 100644 index 286e4e4..0000000 --- a/prepare_cls.sh +++ /dev/null @@ -1,15 +0,0 @@ -#!/usr/bin/env bash - -ROOT=data -DATA_DIR=$ROOT/cls -mkdir -p $DATA_DIR/tmp -echo "Saving data in $DATA_DIR" - -if [ ! -d $DATA_DIR/tmp/cls-acl10-unprocessed ]; then - wget -c http://www.uni-weimar.de/medien/webis/corpora/corpus-webis-cls-10/cls-acl10-unprocessed.tar.gz -P $DATA_DIR/tmp - tar -xzvf $DATA_DIR/tmp/cls-acl10-unprocessed.tar.gz -C $DATA_DIR/tmp/ -else - echo "CLS already exists. Skipping download." -fi - -python ulmfit/postprocess_cls.py --input_dir $DATA_DIR/tmp/cls-acl10-unprocessed --output_dir $DATA_DIR diff --git a/prepare_rcv.sh b/prepare_rcv.sh deleted file mode 100644 index acea5d4..0000000 --- a/prepare_rcv.sh +++ /dev/null @@ -1,50 +0,0 @@ -#!/usr/bin/env bash - -if [[ $# -ne 3 ]] ; then - echo 'Usage: ./prepare_rcv.sh ' - echo 'This dataset has restricted access: apply at https://trec.nist.gov/data/reuters/reuters.html' - exit 1 -fi - -ROOT="data" -DATA_DIR="${ROOT}/rcv" -mkdir -p "${DATA_DIR}/tmp" -echo "Saving data in $DATA_DIR" - -RCV_URL=$1 -RCV_USER=$2 -RCV_PASSWORD=$3 - -MLDOC=https://github.com/facebookresearch/MLDoc/raw/master -wget -c $MLDOC/generate_documents.py -P "${DATA_DIR}/tmp" - -if [ ! -d "${DATA_DIR}/tmp/RCV2_Multilingual_Corpus" ]; then - wget -c --user $RCV_USER --password $RCV_PASSWORD $RCV_URL/rcv2.tar.xz -P "${DATA_DIR}/tmp" - tar xvf "${DATA_DIR}/tmp/rcv2.tar.xz" -C "${DATA_DIR}/tmp/" -else - echo "RCV2 already exists. Skipping download." -fi - -if [ ! -d "${DATA_DIR}/tmp/RCV2_Multilingual_Corpus/english" ]; then - wget -c --user $RCV_USER --password $RCV_PASSWORD $RCV_URL/rcv1.tar.xz -P "${DATA_DIR}/tmp" - tar xvf "${DATA_DIR}/tmp/rcv1.tar.xz" -C "${DATA_DIR}/tmp/RCV2_Multilingual_Corpus/" - mv "${DATA_DIR}/tmp/RCV2_Multilingual_Corpus/rcv1" "${DATA_DIR}/tmp/RCV2_Multilingual_Corpus/english" -else - echo "RCV1 already exists. Skipping download." -fi - -for LANGUAGE in spanish chinese french japanese german italian russian english -do - mkdir -p "${DATA_DIR}/${LANGUAGE}" - for FILE_EXT in train.1000 train.2000 train.5000 train.10000 dev test - do - wget -c $MLDOC/mldoc-indices/$LANGUAGE.$FILE_EXT -P "${DATA_DIR}/tmp" - - python $DATA_DIR/tmp/generate_documents.py \ - --indices-file $DATA_DIR/tmp/$LANGUAGE.$FILE_EXT \ - --output-filename $DATA_DIR/tmp/$LANGUAGE.$FILE_EXT.raw \ - --rcv-dir $DATA_DIR/tmp/RCV2_Multilingual_Corpus/$LANGUAGE - python ulmfit/postprocess_rcv.py --input_file $DATA_DIR/tmp/$LANGUAGE.$FILE_EXT.raw \ - --output_file $DATA_DIR/$LANGUAGE/$FILE_EXT.csv - done -done diff --git a/ulmfit/merge_langs.py b/ulmfit/merge_langs.py deleted file mode 100644 index 7fee7ed..0000000 --- a/ulmfit/merge_langs.py +++ /dev/null @@ -1,35 +0,0 @@ -""" -Script to merge WikiText files created with `create_wikitext.py`. -""" -import fire -from pathlib import Path -from contextlib import ExitStack - -def merge_wikitext(paths, langs, dest_path, num_sentences): - wiki_paths = [Path(path) for path in paths] - for wiki_path in wiki_paths: - assert wiki_path.exists(), f'Error: {wiki_path} does not exist.' - dest_path = Path(dest_path) - dest_path.mkdir(exist_ok=True) - splits = ['train', 'valid', 'test'] - concat_langs = '-'.join(langs) - for split in splits: - with ExitStack() as stack: - files = [stack.enter_context(open( - wiki_path / f'{lang}.wiki.{split}.tokens', 'r', encoding='utf-8')) - for lang, wiki_path in zip(langs, wiki_paths)] - - output = stack.enter_context(open(dest_path / f'{concat_langs}.wiki.{split}.tokens', 'w', encoding='utf-8')) - done = False - while not done: - for file in files: - lines = [file.readline() for x in range(num_sentences)] - size = len(lines) - lines = [line for line in lines if line] - if len(lines) < size: - done = True - for line in lines: - output.write(line) - -if __name__ == '__main__': - fire.Fire(merge_wikitext) \ No newline at end of file diff --git a/ulmfit/postprocess_cls.py b/ulmfit/postprocess_cls.py deleted file mode 100644 index ad55a22..0000000 --- a/ulmfit/postprocess_cls.py +++ /dev/null @@ -1,23 +0,0 @@ -import fire -import pandas as pd -import os -from bs4 import BeautifulSoup - -def main(input_dir, output_dir): - for lang in ['en', 'de', 'fr', 'jp']: - for cat in ['dvd', 'music', 'books']: - for mode in ['train', 'test']: # , 'unlabeled']: - os.makedirs(os.path.join(input_dir, lang), exist_ok=True) - with open(os.path.join(input_dir, lang, cat, mode + '.review'), 'r') as f: - items = BeautifulSoup(f.read(), features="html.parser").find_all('item') - text = [item.find('text').text.strip() for item in items] - summary = [item.find('summary').text.strip() for item in items] - if mode == 'unlabeled': - out = pd.DataFrame({'summary': summary, 'text': text}) - else: - labels = [1 if item.rating.text in ('4.0', '5.0') else 0 for item in items] - out = pd.DataFrame({'labels': labels, 'summary': summary, 'text': text}) - file_name = os.path.join(output_dir, f'{lang}/{cat}.{mode}.csv') - out.to_csv(file_name, header=None, index=False) - -if __name__ == '__main__': fire.Fire(main) diff --git a/ulmfit/postprocess_rcv.py b/ulmfit/postprocess_rcv.py deleted file mode 100644 index 27753a2..0000000 --- a/ulmfit/postprocess_rcv.py +++ /dev/null @@ -1,12 +0,0 @@ -import fire -import pandas as pd - -def main(input_file, output_file): - df = pd.read_csv(input_file, sep='\t', header=None) - unique_labels = sorted(list(df[0].unique())) - labels = [unique_labels.index(label) for label in df[0]] - texts = [eval(text).decode('utf-8').strip() for text in df[1]] - out = pd.DataFrame({'labels': labels, 'texts': texts}) - out.to_csv(output_file, header=None, index=False) - -if __name__ == '__main__': fire.Fire(main)