File size: 3,590 Bytes
2ded227 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 |
# 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_and_extract(URL)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"path": os.path.join(archive, self.config.name, "train.txt"),
},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"path": os.path.join(archive, self.config.name, "valid.txt")
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"path": os.path.join(archive, self.config.name, "test.txt"),
},
),
]
def _generate_examples(self, path):
with open(path, encoding="utf-8") as f:
for _id, line in enumerate(f):
yield _id, { "text": line.strip() } |