Datasets:
Multilinguality:
multilingual
Size Categories:
1K<n<10K
Language Creators:
found
Annotations Creators:
no-annotation
Source Datasets:
original
Tags:
License:
""" | |
https://github.com/pytorch/data/blob/main/examples/text/CC100.ipynb | |
Sample from multi-gigabyte-size compressed dataset without downloading the whole thing | |
This executes very fast | |
""" | |
import time | |
import os | |
from functools import partial | |
from operator import itemgetter | |
from torchdata.datapipes.iter import ( | |
FileOpener, | |
HttpReader, | |
) | |
ROOT_DIR = os.path.expanduser('~/.torchdata/CC100') # This directory needs to be crated and set | |
def _path_fn(root, x): | |
return os.path.join(root, os.path.basename(x).rstrip(".xz")) | |
def _process_tuple(language_code, t): | |
return language_code, t[1].decode() | |
# CC100 support (http://data.statmt.org/cc-100/) | |
URL = "http://data.statmt.org/cc-100/%s.txt.xz" | |
VALID_CODES = [ | |
"am", "ar", "as", "az", "be", "bg", "bn", "bn_rom", "br", "bs", "ca", "cs", "cy", "da", "de", | |
"el", "en", "eo", "es", "et", "eu", "fa", "ff", "fi", "fr", "fy", "ga", "gd", "gl", "gn", "gu", | |
"ha", "he", "hi", "hi_rom", "hr", "ht", "hu", "hy", "id", "ig", "is", "it", "ja", "jv", "ka", | |
"kk", "km", "kn", "ko", "ku", "ky", "la", "lg", "li", "ln", "lo", "lt", "lv", "mg", "mk", "ml", | |
"mn", "mr", "ms", "my", "my_zaw", "ne", "nl", "no", "ns", "om", "or", "pa", "pl", "ps", "pt", | |
"qu", "rm", "ro", "ru", "sa", "si", "sc", "sd", "sk", "sl", "so", "sq", "sr", "ss", "su", "sv", | |
"sw", "ta", "ta_rom", "te", "te_rom", "th", "tl", "tn", "tr", "ug", "uk", "ur", "ur_rom", "uz", | |
"vi", "wo", "xh", "yi", "yo", "zh-Hans", "zh-Hant", "zu", | |
] | |
def CC100(root, language_code, use_caching=True): | |
if language_code not in VALID_CODES: | |
raise ValueError(f"Invalid language code {language_code}") | |
url = URL % language_code | |
if use_caching: | |
cache_compressed_dp = HttpReader([url]).map(itemgetter(0)) | |
cache_compressed_dp = cache_compressed_dp.end_caching(mode="wb", same_filepath_fn=True) | |
cache_decompressed_dp = cache_compressed_dp.on_disk_cache(filepath_fn=partial(_path_fn, root)) | |
cache_decompressed_dp = FileOpener(cache_decompressed_dp).read_from_xz() | |
cache_decompressed_dp = cache_decompressed_dp.end_caching(mode="wb") | |
data_dp = FileOpener(cache_decompressed_dp) | |
else: | |
data_dp = HttpReader([url]).load_from_xz() | |
units_dp = data_dp.readlines().map(partial(_process_tuple, language_code)) | |
return units_dp | |
def download_head_10000(): | |
for lang in VALID_CODES: | |
start_time = time.time() | |
f_out = open(f"{lang}.txt", "w", encoding="utf-8") | |
for i, x in enumerate(CC100(ROOT_DIR, lang, use_caching=False)): | |
if i >= 10000: | |
break | |
f_out.write(x[1] + "\n") | |
print(f"Execution time - {lang} - {(time.time() - start_time):.2f} secs") | |
f_out.close() | |
if __name__ == "__main__": | |
download_head_10000() | |