# Copyright (c) Facebook, Inc. and its affiliates. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import itertools import os import csv from collections import defaultdict from six.moves import zip import io import wget import sys from subprocess import check_call, check_output # scripts and data locations CWD = os.getcwd() UTILS = f"{CWD}/utils" MOSES = f"{UTILS}/mosesdecoder" WORKDIR_ROOT = os.environ.get('WORKDIR_ROOT', None) if WORKDIR_ROOT is None or not WORKDIR_ROOT.strip(): print('please specify your working directory root in OS environment variable WORKDIR_ROOT. Exitting..."') sys.exit(-1) # please donwload mosesdecoder here: detok_cmd = f'{MOSES}/scripts/tokenizer/detokenizer.perl' def call(cmd): print(f"Executing: {cmd}") check_call(cmd, shell=True) class MultiLingualAlignedCorpusReader(object): """A class to read TED talk dataset """ def __init__(self, corpus_path, delimiter='\t', target_token=True, bilingual=True, corpus_type='file', lang_dict={'source': ['fr'], 'target': ['en']}, eval_lang_dict=None, zero_shot=False, detok=True, ): self.empty_line_flag = 'NULL' self.corpus_path = corpus_path self.delimiter = delimiter self.bilingual = bilingual self.lang_dict = lang_dict self.lang_set = set() self.target_token = target_token self.zero_shot = zero_shot self.eval_lang_dict = eval_lang_dict self.corpus_type = corpus_type self.detok = detok for list_ in self.lang_dict.values(): for lang in list_: self.lang_set.add(lang) self.data = dict() self.data['train'] = self.read_aligned_corpus(split_type='train') self.data['test'] = self.read_aligned_corpus(split_type='test') self.data['dev'] = self.read_aligned_corpus(split_type='dev') def read_data(self, file_loc_): data_list = list() with io.open(file_loc_, 'r', encoding='utf8') as fp: for line in fp: try: text = line.strip() except IndexError: text = self.empty_line_flag data_list.append(text) return data_list def filter_text(self, dict_): if self.target_token: field_index = 1 else: field_index = 0 data_dict = defaultdict(list) list1 = dict_['source'] list2 = dict_['target'] for sent1, sent2 in zip(list1, list2): try: src_sent = ' '.join(sent1.split()[field_index: ]) except IndexError: src_sent = 'NULL' if src_sent.find(self.empty_line_flag) != -1 or len(src_sent) == 0: continue elif sent2.find(self.empty_line_flag) != -1 or len(sent2) == 0: continue else: data_dict['source'].append(sent1) data_dict['target'].append(sent2) return data_dict def read_file(self, split_type, data_type): return self.data[split_type][data_type] def save_file(self, path_, split_type, data_type, lang): tok_file = tok_file_name(path_, lang) with io.open(tok_file, 'w', encoding='utf8') as fp: for line in self.data[split_type][data_type]: fp.write(line + '\n') if self.detok: de_tok(tok_file, lang) def add_target_token(self, list_, lang_id): new_list = list() token = '__' + lang_id + '__' for sent in list_: new_list.append(token + ' ' + sent) return new_list def read_from_single_file(self, path_, s_lang, t_lang): data_dict = defaultdict(list) with io.open(path_, 'r', encoding='utf8') as fp: reader = csv.DictReader(fp, delimiter='\t', quoting=csv.QUOTE_NONE) for row in reader: data_dict['source'].append(row[s_lang]) data_dict['target'].append(row[t_lang]) if self.target_token: text = self.add_target_token(data_dict['source'], t_lang) data_dict['source'] = text return data_dict['source'], data_dict['target'] def read_aligned_corpus(self, split_type='train'): data_dict = defaultdict(list) iterable = [] s_list = [] t_list = [] if self.zero_shot: if split_type == "train": iterable = zip(self.lang_dict['source'], self.lang_dict['target']) else: iterable = zip(self.eval_lang_dict['source'], self.eval_lang_dict['target']) elif self.bilingual: iterable = itertools.product(self.lang_dict['source'], self.lang_dict['target']) for s_lang, t_lang in iterable: if s_lang == t_lang: continue if self.corpus_type == 'file': split_type_file_path = os.path.join(self.corpus_path, "all_talks_{}.tsv".format(split_type)) s_list, t_list = self.read_from_single_file(split_type_file_path, s_lang=s_lang, t_lang=t_lang) data_dict['source'] += s_list data_dict['target'] += t_list new_data_dict = self.filter_text(data_dict) return new_data_dict def read_langs(corpus_path): split_type_file_path = os.path.join(corpus_path, 'extracted', "all_talks_dev.tsv") with io.open(split_type_file_path, 'r', encoding='utf8') as fp: reader = csv.DictReader(fp, delimiter='\t', quoting=csv.QUOTE_NONE) header = next(reader) return [k for k in header.keys() if k != 'talk_name'] def extra_english(corpus_path, split): split_type_file_path = os.path.join(corpus_path, f"all_talks_{split}.tsv") output_split_type_file_path = os.path.join(corpus_path, f"all_talks_{split}.en") with io.open(split_type_file_path, 'r', encoding='utf8') as fp, io.open(output_split_type_file_path, 'w', encoding='utf8') as fw: reader = csv.DictReader(fp, delimiter='\t', quoting=csv.QUOTE_NONE) for row in reader: line = row['en'] fw.write(line + '\n') de_tok(output_split_type_file_path, 'en') def tok_file_name(filename, lang): seps = filename.split('.') seps.insert(-1, 'tok') tok_file = '.'.join(seps) return tok_file def de_tok(tok_file, lang): # seps = tok_file.split('.') # seps.insert(-1, 'detok') # de_tok_file = '.'.join(seps) de_tok_file = tok_file.replace('.tok.', '.') cmd = 'perl {detok_cmd} -l {lang} < {tok_file} > {de_tok_file}'.format( detok_cmd=detok_cmd, tok_file=tok_file, de_tok_file=de_tok_file, lang=lang[:2]) call(cmd) def extra_bitex( ted_data_path, lsrc_lang, ltrg_lang, target_token, output_data_path, ): def get_ted_lang(lang): long_langs = ['pt-br', 'zh-cn', 'zh-tw', 'fr-ca'] if lang[:5] in long_langs: return lang[:5] elif lang[:4] =='calv': return lang[:5] elif lang in ['pt_BR', 'zh_CN', 'zh_TW', 'fr_CA']: return lang.lower().replace('_', '-') return lang[:2] src_lang = get_ted_lang(lsrc_lang) trg_lang = get_ted_lang(ltrg_lang) train_lang_dict={'source': [src_lang], 'target': [trg_lang]} eval_lang_dict = {'source': [src_lang], 'target': [trg_lang]} obj = MultiLingualAlignedCorpusReader(corpus_path=ted_data_path, lang_dict=train_lang_dict, target_token=target_token, corpus_type='file', eval_lang_dict=eval_lang_dict, zero_shot=False, bilingual=True) os.makedirs(output_data_path, exist_ok=True) lsrc_lang = lsrc_lang.replace('-', '_') ltrg_lang = ltrg_lang.replace('-', '_') obj.save_file(output_data_path + f"/train.{lsrc_lang}-{ltrg_lang}.{lsrc_lang}", split_type='train', data_type='source', lang=src_lang) obj.save_file(output_data_path + f"/train.{lsrc_lang}-{ltrg_lang}.{ltrg_lang}", split_type='train', data_type='target', lang=trg_lang) obj.save_file(output_data_path + f"/test.{lsrc_lang}-{ltrg_lang}.{lsrc_lang}", split_type='test', data_type='source', lang=src_lang) obj.save_file(output_data_path + f"/test.{lsrc_lang}-{ltrg_lang}.{ltrg_lang}", split_type='test', data_type='target', lang=trg_lang) obj.save_file(output_data_path + f"/valid.{lsrc_lang}-{ltrg_lang}.{lsrc_lang}", split_type='dev', data_type='source', lang=src_lang) obj.save_file(output_data_path + f"/valid.{lsrc_lang}-{ltrg_lang}.{ltrg_lang}", split_type='dev', data_type='target', lang=trg_lang) def bar_custom(current, total, width=80): print("Downloading: %d%% [%d / %d] Ks" % (current / total * 100, current / 1000, total / 1000), end='\r') def download_and_extract(download_to, extract_to): url = 'http://phontron.com/data/ted_talks.tar.gz' filename = f"{download_to}/ted_talks.tar.gz" if os.path.exists(filename): print(f'{filename} has already been downloaded so skip') else: filename = wget.download(url, filename, bar=bar_custom) if os.path.exists(f'{extract_to}/all_talks_train.tsv'): print(f'Already extracted so skip') else: extract_cmd = f'tar xzfv "{filename}" -C "{extract_to}"' call(extract_cmd) if __name__ == "__main__": import argparse parser = argparse.ArgumentParser() parser.add_argument('--ted_data_path', type=str, default=WORKDIR_ROOT, required=False) parser.add_argument( '--direction-list', type=str, # default=None, #for ML50 default=( "bn_IN-en_XX,he_IL-en_XX,fa_IR-en_XX,id_ID-en_XX,sv_SE-en_XX,pt_XX-en_XX,ka_GE-en_XX,ka_GE-en_XX,th_TH-en_XX," "mr_IN-en_XX,hr_HR-en_XX,uk_UA-en_XX,az_AZ-en_XX,mk_MK-en_XX,gl_ES-en_XX,sl_SI-en_XX,mn_MN-en_XX," #non-english directions # "fr_XX-de_DE," # replaced with wmt20 # "ja_XX-ko_KR,es_XX-pt_XX,ru_RU-sv_SE,hi_IN-bn_IN,id_ID-ar_AR,cs_CZ-pl_PL,ar_AR-tr_TR" ), required=False) parser.add_argument('--target-token', action='store_true', default=False) parser.add_argument('--extract-all-english', action='store_true', default=False) args = parser.parse_args() import sys import json # TED Talks data directory ted_data_path = args.ted_data_path download_to = f'{ted_data_path}/downloads' extract_to = f'{ted_data_path}/extracted' #DESTDIR=${WORKDIR_ROOT}/ML50/raw/ output_path = f'{ted_data_path}/ML50/raw' os.makedirs(download_to, exist_ok=True) os.makedirs(extract_to, exist_ok=True) os.makedirs(output_path, exist_ok=True) download_and_extract(download_to, extract_to) if args.extract_all_english: for split in ['train', 'dev', 'test']: extra_english(ted_data_path, split) exit(0) if args.direction_list is not None: directions = args.direction_list.strip().split(',') directions = [tuple(d.strip().split('-', 1)) for d in directions if d] else: langs = read_langs(ted_data_path) # directions = [ # '{}.{}'.format(src, tgt) # for src in langs # for tgt in langs # if src < tgt # ] directions = [('en', tgt) for tgt in langs if tgt != 'en'] print(f'num directions={len(directions)}: {directions}') for src_lang, trg_lang in directions: print('--working on {}-{}'.format(src_lang, trg_lang)) extra_bitex( extract_to, src_lang, trg_lang, target_token=args.target_token, output_data_path=output_path )