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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
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