Datasets:
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# coding=utf-8
# 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.
"""TODO: Add a description here."""
import csv
import glob
import os
import datasets
# TODO: Add BibTeX citation
# Find for instance the citation on arxiv or on the dataset repo/website
_CITATION = """\
@InProceedings{huggingface:c4_200m_dataset,
title = {c4_200m},
author={Li Liwei},
year={2021}
}
"""
_DESCRIPTION = """\
GEC Dataset Generated from C4
"""
_HOMEPAGE = "https://www.kaggle.com/a0155991rliwei/c4-200m"
_LICENSE = ""
_URL = "data.zip"
class C4200M(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.0.0")
DEFAULT_CONFIG_NAME = "train"
def _info(self):
features = datasets.Features(
{
"input": datasets.Value("string"),
"output": datasets.Value("string"),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
supervised_keys=None,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
data_dir = dl_manager.download_and_extract(_URL)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepath": data_dir,
},
),
]
def _generate_examples(
self, filepath
):
""" Yields examples as (key, example) tuples. """
def fix_nulls(s):
for line in s:
yield line.replace('\0', ' ')
path = os.path.join(filepath, "*.tsv*")
for filename in glob.glob(path):
with open(filename, encoding="utf-8") as f:
reader = csv.reader(fix_nulls(f), delimiter="\t", quoting=csv.QUOTE_NONE)
for id_, row in enumerate(reader):
yield id_, {
"input": row[0],
"output": row[1],
} |