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| import os, sys | |
| import glob, itertools | |
| import pandas as pd | |
| 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) | |
| def load_langs(path): | |
| with open(path) as fr: | |
| langs = [l.strip() for l in fr] | |
| return langs | |
| def load_sentences(raw_data, split, direction): | |
| src, tgt = direction.split('-') | |
| src_path = f"{raw_data}/{split}.{direction}.{src}" | |
| tgt_path = f"{raw_data}/{split}.{direction}.{tgt}" | |
| if os.path.exists(src_path) and os.path.exists(tgt_path): | |
| return [(src, open(src_path).read().splitlines()), (tgt, open(tgt_path).read().splitlines())] | |
| else: | |
| return [] | |
| def swap_direction(d): | |
| src, tgt = d.split('-') | |
| return f'{tgt}-{src}' | |
| def get_all_test_data(raw_data, directions, split='test'): | |
| test_data = [ | |
| x | |
| for dd in directions | |
| for d in [dd, swap_direction(dd)] | |
| for x in load_sentences(raw_data, split, d) | |
| ] | |
| # all_test_data = {s for _, d in test_data for s in d} | |
| all_test_data = {} | |
| for lang, d in test_data: | |
| for s in d: | |
| s = s.strip() | |
| lgs = all_test_data.get(s, set()) | |
| lgs.add(lang) | |
| all_test_data[s] = lgs | |
| return all_test_data, test_data | |
| def check_train_sentences(raw_data, direction, all_test_data, mess_up_train={}): | |
| src, tgt = direction.split('-') | |
| tgt_path = f"{raw_data}/train.{direction}.{tgt}" | |
| src_path = f"{raw_data}/train.{direction}.{src}" | |
| print(f'check training data in {raw_data}/train.{direction}') | |
| size = 0 | |
| if not os.path.exists(tgt_path) or not os.path.exists(src_path): | |
| return mess_up_train, size | |
| with open(src_path) as f, open(tgt_path) as g: | |
| for src_line, tgt_line in zip(f, g): | |
| s = src_line.strip() | |
| t = tgt_line.strip() | |
| size += 1 | |
| if s in all_test_data: | |
| langs = mess_up_train.get(s, set()) | |
| langs.add(direction) | |
| mess_up_train[s] = langs | |
| if t in all_test_data: | |
| langs = mess_up_train.get(t, set()) | |
| langs.add(direction) | |
| mess_up_train[t] = langs | |
| return mess_up_train, size | |
| def check_train_all(raw_data, directions, all_test_data): | |
| mess_up_train = {} | |
| data_sizes = {} | |
| for direction in directions: | |
| _, size = check_train_sentences(raw_data, direction, all_test_data, mess_up_train) | |
| data_sizes[direction] = size | |
| return mess_up_train, data_sizes | |
| def count_train_in_other_set(mess_up_train): | |
| train_in_others = [(direction, s) for s, directions in mess_up_train.items() for direction in directions] | |
| counts = {} | |
| for direction, s in train_in_others: | |
| counts[direction] = counts.get(direction, 0) + 1 | |
| return counts | |
| def train_size_if_remove_in_otherset(data_sizes, mess_up_train): | |
| counts_in_other = count_train_in_other_set(mess_up_train) | |
| remain_sizes = [] | |
| for direction, count in counts_in_other.items(): | |
| remain_sizes.append((direction, data_sizes[direction] - count, data_sizes[direction], count, 100 * count / data_sizes[direction] )) | |
| return remain_sizes | |
| def remove_messed_up_sentences(raw_data, direction, mess_up_train, mess_up_train_pairs, corrected_langs): | |
| split = 'train' | |
| src_lang, tgt_lang = direction.split('-') | |
| tgt = f"{raw_data}/{split}.{direction}.{tgt_lang}" | |
| src = f"{raw_data}/{split}.{direction}.{src_lang}" | |
| print(f'working on {direction}: ', src, tgt) | |
| if not os.path.exists(tgt) or not os.path.exists(src) : | |
| return | |
| corrected_tgt = f"{to_folder}/{split}.{direction}.{tgt_lang}" | |
| corrected_src = f"{to_folder}/{split}.{direction}.{src_lang}" | |
| line_num = 0 | |
| keep_num = 0 | |
| with open(src, encoding='utf8',) as fsrc, \ | |
| open(tgt, encoding='utf8',) as ftgt, \ | |
| open(corrected_src, 'w', encoding='utf8') as fsrc_corrected, \ | |
| open(corrected_tgt, 'w', encoding='utf8') as ftgt_corrected: | |
| for s, t in zip(fsrc, ftgt): | |
| s = s.strip() | |
| t = t.strip() | |
| if t not in mess_up_train \ | |
| and s not in mess_up_train \ | |
| and (s, t) not in mess_up_train_pairs \ | |
| and (t, s) not in mess_up_train_pairs: | |
| corrected_langs.add(direction) | |
| print(s, file=fsrc_corrected) | |
| print(t, file=ftgt_corrected) | |
| keep_num += 1 | |
| line_num += 1 | |
| if line_num % 1000 == 0: | |
| print(f'completed {line_num} lines', end='\r') | |
| return line_num, keep_num | |
| ########## | |
| def merge_valid_test_messup(mess_up_train_valid, mess_up_train_test): | |
| merged_mess = [] | |
| for s in set(list(mess_up_train_valid.keys()) + list(mess_up_train_test.keys())): | |
| if not s: | |
| continue | |
| valid = mess_up_train_valid.get(s, set()) | |
| test = mess_up_train_test.get(s, set()) | |
| merged_mess.append((s, valid | test)) | |
| return dict(merged_mess) | |
| ######### | |
| def check_train_pairs(raw_data, direction, all_test_data, mess_up_train={}): | |
| src, tgt = direction.split('-') | |
| #a hack; TODO: check the reversed directions | |
| path1 = f"{raw_data}/train.{src}-{tgt}.{src}" | |
| path2 = f"{raw_data}/train.{src}-{tgt}.{tgt}" | |
| if not os.path.exists(path1) or not os.path.exists(path2) : | |
| return | |
| with open(path1) as f1, open(path2) as f2: | |
| for src_line, tgt_line in zip(f1, f2): | |
| s = src_line.strip() | |
| t = tgt_line.strip() | |
| if (s, t) in all_test_data or (t, s) in all_test_data: | |
| langs = mess_up_train.get( (s, t), set()) | |
| langs.add(src) | |
| langs.add(tgt) | |
| mess_up_train[(s, t)] = langs | |
| def load_pairs(raw_data, split, direction): | |
| src, tgt = direction.split('-') | |
| src_f = f"{raw_data}/{split}.{direction}.{src}" | |
| tgt_f = f"{raw_data}/{split}.{direction}.{tgt}" | |
| if tgt != 'en_XX': | |
| src_f, tgt_f = tgt_f, src_f | |
| if os.path.exists(src_f) and os.path.exists(tgt_f): | |
| return list(zip(open(src_f).read().splitlines(), | |
| open(tgt_f).read().splitlines(), | |
| )) | |
| else: | |
| return [] | |
| # skip_langs = ['cs_CZ', 'en_XX', 'tl_XX', 'tr_TR'] | |
| def get_messed_up_test_pairs(split, directions): | |
| test_pairs = [ | |
| (d, load_pairs(raw_data, split, d)) | |
| for d in directions | |
| ] | |
| # all_test_data = {s for _, d in test_data for s in d} | |
| all_test_pairs = {} | |
| for direction, d in test_pairs: | |
| src, tgt = direction.split('-') | |
| for s in d: | |
| langs = all_test_pairs.get(s, set()) | |
| langs.add(src) | |
| langs.add(tgt) | |
| all_test_pairs[s] = langs | |
| mess_up_train_pairs = {} | |
| for direction in directions: | |
| check_train_pairs(raw_data, direction, all_test_pairs, mess_up_train_pairs) | |
| return all_test_pairs, mess_up_train_pairs | |
| if __name__ == "__main__": | |
| ####### | |
| import argparse | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument( | |
| '--from-folder', | |
| required=True, | |
| type=str) | |
| parser.add_argument( | |
| '--to-folder', | |
| required=True, | |
| type=str) | |
| parser.add_argument( | |
| '--directions', | |
| default=None, | |
| type=str) | |
| args = parser.parse_args() | |
| raw_data = args.from_folder | |
| to_folder = args.to_folder | |
| os.makedirs(to_folder, exist_ok=True) | |
| if args.directions: | |
| directions = args.directions.split(',') | |
| else: | |
| raw_files = itertools.chain( | |
| glob.glob(f'{raw_data}/train*'), | |
| glob.glob(f'{raw_data}/valid*'), | |
| glob.glob(f'{raw_data}/test*'), | |
| ) | |
| directions = [os.path.split(file_path)[-1].split('.')[1] for file_path in raw_files] | |
| print('working on directions: ', directions) | |
| ########## | |
| all_test_data, test_data = get_all_test_data(raw_data, directions, 'test') | |
| print('==loaded test data==') | |
| all_valid_data, valid_data = get_all_test_data(raw_data, directions, 'valid') | |
| print('==loaded valid data==') | |
| all_valid_test_data = merge_valid_test_messup(all_test_data, all_valid_data) | |
| mess_up_train, data_sizes = check_train_all(raw_data, directions, all_valid_test_data) | |
| print('training messing up with valid, test data:', len(mess_up_train)) | |
| data_situation = train_size_if_remove_in_otherset(data_sizes, mess_up_train) | |
| df = pd.DataFrame(data_situation, columns=['direction', 'train_size_after_remove', 'orig_size', 'num_to_remove', 'remove_percent']) | |
| df.sort_values('remove_percent', ascending=False) | |
| df.to_csv(f'{raw_data}/clean_summary.tsv', sep='\t') | |
| print(f'projected data clean summary in: {raw_data}/clean_summary.tsv') | |
| # correct the dataset: | |
| all_test_pairs, mess_up_test_train_pairs = get_messed_up_test_pairs('test', directions) | |
| all_valid_pairs, mess_up_valid_train_pairs = get_messed_up_test_pairs('valid', directions) | |
| all_messed_pairs = set(mess_up_test_train_pairs.keys()).union(set(mess_up_valid_train_pairs.keys())) | |
| corrected_directions = set() | |
| real_data_situation = [] | |
| for direction in directions: | |
| org_size, new_size = remove_messed_up_sentences(raw_data, direction, mess_up_train, all_messed_pairs, corrected_directions) | |
| if org_size == 0: | |
| print(f"{direction} has size 0") | |
| continue | |
| real_data_situation.append( | |
| (direction, new_size, org_size, org_size - new_size, (org_size - new_size) / org_size * 100) | |
| ) | |
| print('corrected directions: ', corrected_directions) | |
| df = pd.DataFrame(real_data_situation, columns=['direction', 'train_size_after_remove', 'orig_size', 'num_to_remove', 'remove_percent']) | |
| df.sort_values('remove_percent', ascending=False) | |
| df.to_csv(f'{raw_data}/actual_clean_summary.tsv', sep='\t') | |
| print(f'actual data clean summary (which can be different from the projected one because of duplications) in: {raw_data}/actual_clean_summary.tsv') | |
| import shutil | |
| for direction in directions: | |
| src_lang, tgt_lang = direction.split('-') | |
| for split in ['train', 'valid', 'test']: | |
| # copying valid, test and uncorrected train | |
| if direction in corrected_directions and split == 'train': | |
| continue | |
| tgt = f"{raw_data}/{split}.{direction}.{tgt_lang}" | |
| src = f"{raw_data}/{split}.{direction}.{src_lang}" | |
| if not (os.path.exists(src) and os.path.exists(tgt)): | |
| continue | |
| corrected_tgt = f"{to_folder}/{split}.{direction}.{tgt_lang}" | |
| corrected_src = f"{to_folder}/{split}.{direction}.{src_lang}" | |
| print(f'copying {src} to {corrected_src}') | |
| shutil.copyfile(src, corrected_src) | |
| print(f'copying {tgt} to {corrected_tgt}') | |
| shutil.copyfile(tgt, corrected_tgt) | |
| print('completed') |