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# coding=utf-8
# Copyright 2023 Devrim Cavusoglu and the HuggingFace Datasets Authors.
#
# 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.
# Lint as: python3
"""Wiki Long Subset."""
import json
import datasets
logger = datasets.logging.get_logger(__name__)
_DESCRIPTION = """\
Dataset consisting of long wikipedia articles.
"""
_URLS = {
"train": [
"train/partition_0.jsonl",
"train/partition_1.jsonl",
"train/partition_2.jsonl",
"train/partition_3.jsonl",
"train/partition_4.jsonl",
"train/partition_5.jsonl",
"train/partition_6.jsonl",
"train/partition_7.jsonl",
"train/partition_8.jsonl",
"train/partition_9.jsonl",
"train/partition_10.jsonl",
"train/partition_11.jsonl",
],
"test": "test/partition_0.jsonl",
}
class WikiLongDatasetConfig(datasets.BuilderConfig):
"""BuilderConfig for Dataset."""
def __init__(self, **kwargs):
"""BuilderConfig for Dataset.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(WikiLongDatasetConfig, self).__init__(**kwargs)
@property
def features(self):
return {
"id": datasets.Value("string"),
"url": datasets.Value("string"),
"title": datasets.Value("string"),
"text": datasets.Value("string"),
}
class WikiLongDataset(datasets.GeneratorBasedBuilder):
"""WikiLongDataset Classification dataset. Version 1.0."""
BUILDER_CONFIGS = [
WikiLongDatasetConfig(
version=datasets.Version("1.0.0", ""),
description="Long Wikipedia Articles"
)
]
BUILDER_CONFIG_CLASS = WikiLongDatasetConfig
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(self.config.features),
)
def _split_generators(self, dl_manager):
data_dir = dl_manager.download_and_extract(_URLS)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_dir["train"]}),
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": data_dir["test"]}),
]
def _generate_examples(self, filepath):
"""This function returns the examples in the raw (text) form."""
logger.info("generating examples from = %s", filepath)
if isinstance(filepath, str):
filepath = [filepath]
key = 0
for path in filepath:
with open(path, encoding="utf-8") as data:
for article in data:
yield key, json.loads(article)
key += 1
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