# coding=utf-8 | |
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. | |
# | |
# 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. | |
"""German Common Crawl""" | |
from __future__ import absolute_import, division, print_function | |
import datasets | |
import itertools | |
import gzip | |
from ast import literal_eval | |
# Find for instance the citation on arxiv or on the dataset repo/website | |
_CITATION = """\ | |
@inproceedings{wenzek2020ccnet, | |
title={CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data}, | |
author={Wenzek, Guillaume and Lachaux, Marie-Anne and Conneau, Alexis and Chaudhary, Vishrav and Guzm{\'a}n, Francisco and Joulin, Armand and Grave, {\'E}douard}, | |
booktitle={Proceedings of The 12th Language Resources and Evaluation Conference}, | |
pages={4003--4012}, | |
year={2020} | |
} | |
""" | |
_DESCRIPTION = """\ | |
German Only Extract from Common Crawl | |
This Dataset is for pretraining a German Language Model (Unsupervised) or tune a Multilingual Model specifically to German | |
""" | |
REPO_URL = "https://huggingface.co/datasets/flax-community/german_common_crawl/resolve/main/" | |
_URL_FIRST = [REPO_URL + file_name for file_name in [ | |
"de_head_0000_2015-48.txt.gz", | |
]] | |
_URL_HEAD = [REPO_URL + file_name for file_name in [ | |
"de_head_0000_2015-48.txt.gz", | |
# "de_head_0000_2016-18.txt.gz", | |
# "de_head_0000_2016-44.txt.gz", | |
# "de_head_0000_2017-13.txt.gz", | |
# "de_head_0000_2017-30.txt.gz", | |
# "de_head_0000_2017-39.txt.gz", | |
# "de_head_0000_2017-51.txt.gz", | |
# "de_head_0000_2018-09.txt.gz", | |
# "de_head_0000_2018-17.txt.gz", | |
# "de_head_0000_2018-30.txt.gz", | |
# "de_head_0000_2018-39.txt.gz", | |
# "de_head_0000_2018-51.txt.gz", | |
# "de_head_0000_2019-18.txt.gz", | |
# "de_head_0000_2019-30.txt.gz", | |
# "de_head_0000_2019-47.txt.gz", | |
# "de_head_0000_2020-10.txt.gz", | |
# "de_head_0001_2016-44.txt.gz", | |
# "de_head_0001_2017-13.txt.gz", | |
# "de_head_0001_2017-30.txt.gz", | |
# "de_head_0001_2017-39.txt.gz", | |
# "de_head_0001_2017-51.txt.gz", | |
# "de_head_0001_2018-09.txt.gz", | |
# "de_head_0001_2018-17.txt.gz", | |
# "de_head_0001_2018-30.txt.gz", | |
# "de_head_0001_2018-39.txt.gz", | |
# "de_head_0001_2018-51.txt.gz", | |
# "de_head_0001_2019-09.txt.gz", | |
# "de_head_0001_2019-18.txt.gz", | |
# "de_head_0001_2019-30.txt.gz", | |
# "de_head_0001_2019-47.txt.gz", | |
# "de_head_0001_2020-10.txt.gz", | |
# "de_head_0002_2016-44.txt.gz", | |
# "de_head_0002_2017-13.txt.gz", | |
# "de_head_0002_2017-30.txt.gz", | |
# "de_head_0002_2017-39.txt.gz", | |
# "de_head_0002_2017-51.txt.gz", | |
# "de_head_0002_2018-09.txt.gz", | |
# "de_head_0002_2018-17.txt.gz", | |
# "de_head_0002_2018-30.txt.gz", | |
# "de_head_0002_2018-39.txt.gz", | |
# "de_head_0002_2018-51.txt.gz", | |
# "de_head_0002_2019-09.txt.gz", | |
# "de_head_0002_2019-18.txt.gz", | |
# "de_head_0002_2019-30.txt.gz", | |
# "de_head_0002_2019-47.txt.gz", | |
# "de_head_0002_2020-10.txt.gz", | |
# "de_head_0003_2016-44.txt.gz", | |
# "de_head_0003_2017-13.txt.gz", | |
# "de_head_0003_2017-30.txt.gz", | |
# "de_head_0003_2017-39.txt.gz", | |
# "de_head_0003_2017-51.txt.gz", | |
# "de_head_0003_2018-09.txt.gz", | |
# "de_head_0003_2018-17.txt.gz", | |
# "de_head_0003_2018-30.txt.gz", | |
# "de_head_0003_2018-39.txt.gz", | |
# "de_head_0003_2018-51.txt.gz", | |
# "de_head_0003_2019-09.txt.gz", | |
# "de_head_0003_2019-18.txt.gz", | |
# "de_head_0003_2019-30.txt.gz", | |
# "de_head_0003_2019-47.txt.gz", | |
# "de_head_0003_2020-10.txt.gz", | |
# "de_head_0004_2016-44.txt.gz", | |
# "de_head_0004_2017-30.txt.gz", | |
# "de_head_0004_2017-39.txt.gz", | |
# "de_head_0004_2017-51.txt.gz", | |
# "de_head_0004_2018-09.txt.gz", | |
# "de_head_0004_2018-17.txt.gz", | |
# "de_head_0004_2018-30.txt.gz", | |
# "de_head_0004_2018-39.txt.gz", | |
# "de_head_0004_2018-51.txt.gz", | |
# "de_head_0004_2019-09.txt.gz", | |
# "de_head_0004_2019-18.txt.gz", | |
# "de_head_0004_2019-30.txt.gz", | |
# "de_head_0004_2019-47.txt.gz", | |
# "de_head_0004_2020-10.txt.gz", | |
# "de_head_0005_2017-51.txt.gz", | |
# "de_head_0005_2018-09.txt.gz", | |
# "de_head_0005_2018-17.txt.gz", | |
# "de_head_0005_2018-30.txt.gz", | |
# "de_head_0005_2018-39.txt.gz", | |
# "de_head_0005_2018-51.txt.gz", | |
# "de_head_0005_2019-09.txt.gz", | |
# "de_head_0005_2019-18.txt.gz", | |
# "de_head_0005_2019-30.txt.gz", | |
# "de_head_0005_2019-47.txt.gz", | |
# "de_head_0005_2020-10.txt.gz", | |
# "de_head_0006_2018-09.txt.gz", | |
# "de_head_0006_2018-17.txt.gz", | |
# "de_head_0006_2018-30.txt.gz", | |
# "de_head_0006_2018-39.txt.gz", | |
# "de_head_0006_2018-51.txt.gz", | |
# "de_head_0006_2019-09.txt.gz", | |
# "de_head_0006_2019-18.txt.gz", | |
# "de_head_0006_2019-30.txt.gz", | |
# "de_head_0006_2019-47.txt.gz", | |
# "de_head_0006_2020-10.txt.gz", | |
# "de_head_0007_2018-30.txt.gz", | |
# "de_head_0007_2018-51.txt.gz", | |
# "de_head_0007_2019-09.txt.gz", | |
# "de_head_0007_2019-18.txt.gz", | |
# "de_head_0007_2019-47.txt.gz", | |
# "de_head_0007_2020-10.txt.gz", | |
]] | |
class GermanCommonCrawl(datasets.GeneratorBasedBuilder): | |
"""TODO: Short description of my dataset.""" | |
VERSION = datasets.Version("1.1.0") | |
BUILDER_CONFIGS = [ | |
datasets.BuilderConfig(name="first", version=VERSION, description="Only the first data file"), | |
datasets.BuilderConfig(name="head", version=VERSION, description="Only the head data"), | |
# datasets.BuilderConfig(name="middle", version=VERSION, description="Only the website text without metadata"), | |
# datasets.BuilderConfig(name="all", version=VERSION, description="Only the website text without metadata"), | |
] | |
def _info(self): | |
features = datasets.Features( | |
{ | |
"url": datasets.Value("string"), | |
"date_download": datasets.Value("string"), | |
"digest": datasets.Value("string"), | |
"length": datasets.Value("int32"), | |
"nlines": datasets.Value("int32"), | |
"source_domain": datasets.Value("string"), | |
"title": datasets.Value("string"), | |
"raw_content": datasets.Value("string"), | |
"cc_segment": datasets.Value("string"), | |
"original_nlines": datasets.Value("int32"), | |
"original_length": datasets.Value("int32"), | |
"language": datasets.Value("string"), | |
"language_score": datasets.Value("int32"), | |
"perplexity": datasets.Value("int32"), | |
"bucket": datasets.Value("string"), | |
} | |
) | |
return datasets.DatasetInfo( | |
# This is the description that will appear on the datasets page. | |
description=_DESCRIPTION, | |
# This defines the different columns of the dataset and their types | |
features=features, # Here we define them above because they are different between the two configurations | |
# If there's a common (input, txtget) tuple from the features, | |
# specify them here. They'll be used if as_supervised=True in | |
# builder.as_dataset. | |
supervised_keys=None, | |
# Citation for the dataset | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
if self.config.name == "first": | |
data_files = dl_manager.download(_URL_FIRST) | |
else: | |
raise NotImplementedError("just `first` works for now") | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={ | |
"data_files": data_files, | |
}, | |
), | |
] | |
def _generate_examples(self, data_files): | |
"""This function returns the examples in the raw (text) form by iterating on all the files.""" | |
for filepath in data_files: | |
with gzip.open(filepath, "rt", encoding="utf-8") as f: | |
for id_, line in enumerate(f): | |
item = literal_eval(line) | |
import ipdb; ipdb.set_trace() | |
yield id_, { | |
} | |