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simplebooks / simplebooks.py

Andreas Sünder

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	# 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.

	"""SimpleBooks dataset."""


	import os

	import datasets

	_CITATION = """\
	@misc{nguyen2019simplebooks,
	title={SimpleBooks: Long-term dependency book dataset with simplified English vocabulary for word-level language modeling},
	author={Huyen Nguyen},
	year={2019},
	eprint={1911.12391},
	archivePrefix={arXiv},
	primaryClass={cs.CL}
	}
	"""

	_DESCRIPTION = """\
	SimpleBooks is a small long-term dependency dataset that has the FREQ number equivalent to the 1 billion token dataset. Its small vocabulary size and small percentage of out-of-vocabulary words make it an ideal testbed and benchmark for word-level language modeling task and tutorials.
	It was created from 1,573 Gutenberg books. They were selected out of 39,432 Gutenberg books using a hill-climbing algorithm to maximize FREQ.
	"""

	_LICENSE = "CC BY-SA"

	URL = "https://dldata-public.s3.us-east-2.amazonaws.com/simplebooks.zip"


	class SimpleBooks(datasets.GeneratorBasedBuilder):
	"""SimpleBooks dataset."""

	VERSION = datasets.Version("1.0.0")

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(
	name="simplebooks-2",
	version=VERSION,
	description="2.2M tokens with the vocab size of 11,492",
	),
	datasets.BuilderConfig(
	name="simplebooks-2-raw",
	version=VERSION,
	description="2.2M tokens with the vocab size of 11,492 (raw)",
	),
	datasets.BuilderConfig(
	name="simplebooks-92",
	version=VERSION,
	description="92M tokens with the vocab size of 98,304",
	),
	datasets.BuilderConfig(
	name="simplebooks-92-raw",
	version=VERSION,
	description="92M tokens with the vocab size of 98,304 (raw)",
	),
	]

	DEFAULT_CONFIG_NAME = "simplebooks-2"

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"text": datasets.Value("string"),
	}
	),
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	archive = dl_manager.download(URL)

	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"subset": self.config.name,
	"split": "train",
	"files": dl_manager.iter_archive(archive),
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={
	"subset": self.config.name,
	"split": "valid",
	"files": dl_manager.iter_archive(archive),
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={
	"subset": self.config.name,
	"split": "test",
	"files": dl_manager.iter_archive(archive),
	},
	),
	]

	def _generate_examples(self, subset, split, files):
	_id = 0
	for path, file in files:
	head, tail = os.path.split(path)
	if head.endswith(f"{subset}") and tail == f"{split}.txt":
	for line in file:
	yield _id, {"text": line.strip()}
	_id += 1