# 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 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_2016-44.jsonl", # "dummy.txt.gz", ]] #TODO convert & upload all those files correctly _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", ]] # TOOD add file names and convert and upload all of them _URL_MIDDLE = [REPO_URL + file_name for file_name in [ ]] 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=""), #TODO fill description datasets.BuilderConfig(name="middle", version=VERSION, description=""), #TODO fill description datasets.BuilderConfig(name="all", version=VERSION, description=""), #TODO fill description ] 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) elif self.config.name == "head": data_files = dl_manager.download(_URL_HEAD) elif self.config.name == "middle": data_files = dl_manager.download(_URL_MIDDLE) else: data_files = dl_manager.download(_URL_HEAD + _URL_MIDDLE) 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 open(filepath, "rt", encoding="utf-8") as f: # with gzip.open(filepath, "rt", encoding="utf-8") as f: for id_, line in enumerate(f): item = literal_eval(line) yield id_, { "url": item["url"], "date_download": item["date_download"], "digest": item["digest"], "length": item["length"], "nlines": item["nlines"], "source_domain": item["source_domain"], "title": item["title"], "raw_content": item["raw_content"], "cc_segment": item["cc_segment"], "original_nlines": item["original_nlines"], "original_length": item["original_length"], "language": item["language"], "language_score": item["language_score"], "perplexity": item["perplexity"], "bucket": item["bucket"], }