build script
Browse files- openwebtext-10k.py +89 -0
- process.txt +57 -0
openwebtext-10k.py
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# coding=utf-8
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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""The Open WebText Corpus"""
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import os
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import re
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from itertools import chain
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import datasets
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_CITATION = """\
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@misc{Gokaslan2019OpenWeb,
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title={OpenWebText Corpus},
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author={Aaron Gokaslan*, Vanya Cohen*, Ellie Pavlick, Stefanie Tellex},
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howpublished{\\url{http://Skylion007.github.io/OpenWebTextCorpus}},
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year={2019}
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}
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"""
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_DESCRIPTION = """\
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An open-source replication of the WebText dataset from OpenAI.
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This is a small subset representing the first 10K records from the original dataset - created for testing.
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The full 8M-record dataset is at https://huggingface.co/datasets/openwebtext
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"""
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_URL = "https://cdn-datasets.huggingface.co/nlp/datasets/openwebtext/openwebtext-10k.tar.xz"
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class Openwebtext(datasets.GeneratorBasedBuilder):
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"""The Open WebText dataset."""
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(
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name="plain_text",
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description="Plain text",
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version=datasets.Version("1.0.0"),
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)
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]
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features({"text": datasets.Value("string")}),
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homepage="https://skylion007.github.io/OpenWebTextCorpus/",
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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dl_dir = dl_manager.download_and_extract(_URL)
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owt_dir = os.path.join(dl_dir, "openwebtext-10k")
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subset_xzs = [
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os.path.join(owt_dir, file_name)
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for file_name in sorted(os.listdir(owt_dir))
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if file_name.endswith("xz") # filter out ...xz.lock
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]
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ex_dirs = dl_manager.extract(subset_xzs, num_proc=round(os.cpu_count() * 0.75))
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nested_txt_files = [
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[
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os.path.join(ex_dir, txt_file_name)
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for txt_file_name in sorted(os.listdir(ex_dir))
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if txt_file_name.endswith("txt")
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]
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for ex_dir in ex_dirs
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]
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txt_files = chain(*nested_txt_files)
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return [
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"txt_files": txt_files}),
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]
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def _generate_examples(self, txt_files):
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"""Yields examples."""
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for idx, filepath in enumerate(txt_files):
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with open(filepath, encoding="utf-8") as f:
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yield idx, {"text": re.sub("\n\n\n+", "\n\n", f.read()).strip()}
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process.txt
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# this is a small derivative from 8M-big openwebtext dataset for testing
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# how this build script and dataset_infos.json were generated
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#
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mkdir openwebtext-10k
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cd openwebtext-10k
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# data
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wget https://zenodo.org/record/3834942/files/openwebtext.tar.xz
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tar xf openwebtext.tar.xz
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cd openwebtext
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rename.pl 's|-|-00|; s|-00(\d\d\d)|-$1|; s|-00(\d\d)|-0$1|;' *xz
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# now open the first 30 archives
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mkdir subset
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cp urlsf_subset00-0[0-2]*_data.xz subset
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cd subset
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find . -name "*xz" -exec tar xf {} \;
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mkdir 10k
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find . -name "*txt" | sort | head -10000 | xargs mv -t 10k
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tar cfJ 10k.xz -C 10k .
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mkdir openwebtext-10k
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mv 10k.xz openwebtext-10k
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tar cfJ openwebtext-10k.tar.xz openwebtext-10k
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# the openwebtext subdir gets created on the fly
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aws s3 cp openwebtext-10k.tar.xz s3://datasets.huggingface.co/nlp/datasets/openwebtext/
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# script
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wget https://raw.githubusercontent.com/huggingface/datasets/master/datasets/openwebtext/openwebtext.py
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mv openwebtext.py openwebtext-10k.py
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perl -pi -e 's|openwebtext|openwebtext-10k|g' openwebtext-10k.py
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perl -pi -e 's|https://zenodo.org/record/3834942/files/|https://cdn-datasets.huggingface.co/nlp/datasets/openwebtext/|g' openwebtext-10k.py
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# manually check that the script is correct - edit the descriptions
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# create a new dataset entry on the hub
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https://huggingface.co/new-dataset
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# clone
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git clone https://huggingface.co/datasets/stas/openwebtext-10k
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cp openwebtext-10k.py process.txt openwebtext-10k
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cd openwebtext-10k
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git add openwebtext-10k.py process.txt
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git commit -m "build script" openwebtext-10k.py process.txt
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git push
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# finally test
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datasets-cli test stas/openwebtext-10k --save_infos --all_configs
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# add push the generated config
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git add dataset_infos.json
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git commit -m "add dataset_infos.json" dataset_infos.json
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git push
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