Datasets:
the_pile_stack_exchange

	# coding=utf-8
	# Copyright 2021 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.
	"""The Stack Exchange Corpus"""
	import io
	import os
	import zipfile
	from pathlib import Path

	import datasets
	from datasets.exceptions import DefunctDatasetError


	_CITATION = """\
	@article{pile,
	title={The {P}ile: An 800GB Dataset of Diverse Text for Language Modeling},
	author={Gao, Leo and Biderman, Stella and Black, Sid and Golding, Laurence and Hoppe, Travis and Foster, Charles and Phang, Jason and He, Horace and Thite, Anish and Nabeshima, Noa and Presser, Shawn and Leahy, Connor},
	journal={arXiv preprint arXiv:2101.00027},
	year={2020}
	}
	"""

	_DESCRIPTION = """\
	This dataset is part of EleutherAI/The Pile dataset and is a dataset for Language Models from processing stackexchange data dump, \
	which is an anonymized dump of all user-contributed content on the Stack Exchange network.
	"""

	_HOST_URL = "https://the-eye.eu"
	_URL = f"{_HOST_URL}/public/AI/pile_preliminary_components/stackexchange_dataset.tar"


	class ThePileStackExchange(datasets.GeneratorBasedBuilder):
	"""The StackExchange dataset."""

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(
	name="plain_text",
	description="Plain text",
	version=datasets.Version("1.0.0"),
	)
	]

	def _info(self):
	raise DefunctDatasetError(
	"Dataset 'the_pile_stack_exchange' is defunct and no longer accessible due to unavailability of the source data"
	)
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features({"domain": datasets.Value("string"), "text": datasets.Value("string")}),
	homepage="https://github.com/EleutherAI/stackexchange-dataset",
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	if dl_manager.is_streaming:
	archive = dl_manager.download(_URL)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"files": dl_manager.iter_archive(archive),
	"is_streaming": dl_manager.is_streaming,
	},
	),
	]
	else:
	dl_dir = dl_manager.download_and_extract(_URL)
	zips = [str(f) for f in (Path(dl_dir) / "out").iterdir()]
	extracted = dl_manager.extract(zips, num_proc=os.cpu_count())
	# non-dir extracteds are zero-size unknown things
	dirs = [path for path in extracted if os.path.isdir(path)]
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"files": dl_manager.iter_files(dirs),
	"is_streaming": dl_manager.is_streaming,
	},
	),
	]

	def _generate_examples(self, files, is_streaming):
	"""Yields examples."""
	if is_streaming:
	_id = 0
	for path, file in files:
	if not path.startswith("out/"):
	continue
	file_content = file.read()
	with zipfile.ZipFile(io.BytesIO(file_content)) as zip_file:
	for name in zip_file.namelist():
	if not name.endswith(".txt"):
	continue
	domain = name.split(".")[0]
	with zip_file.open(name, mode="r") as f:
	document = f.read().decode(encoding="utf-8")
	yield _id, {"domain": domain, "text": document}
	_id += 1
	else:
	_id = 0
	for file in files:
	path = Path(file)
	if not path.name.endswith(".txt"):
	continue
	domain = path.name.split(".")[0]
	with path.open(mode="r", encoding="utf-8") as f:
	document = f.read()
	yield _id, {"domain": domain, "text": document}
	_id += 1