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.
"""Pclue dataset."""
import json
import py7zr
import datasets
_CITATION = """https://github.com/CLUEbenchmark/pCLUE"""
_DESCRIPTION = """https://github.com/CLUEbenchmark/pCLUE"""
_HOMEPAGE = "https://github.com/CLUEbenchmark/pCLUE"
_LICENSE = "apache-2.0"
_URL = "https://huggingface.co/datasets/wbbbbb/pclue/resolve/main/pclue.7z"
class Pclue(datasets.GeneratorBasedBuilder):
"""Pclue Corpus dataset."""
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="pclue"),
]
def _info(self):
features = datasets.Features(
{
"input": datasets.Value("string"),
"target": datasets.Value("string"),
"type": 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."""
path = dl_manager.download_and_extract(_URL)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepath": path+"train.json",
"split": "train",
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"filepath": path+"test.json",
"split": "test",
},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"filepath": path+"dev.json",
"split": "val",
},
),
]
def _generate_examples(self, filepath, split):
"""Yields examples."""
with open(filepath, encoding="utf-8") as f:
for idx, row in enumerate(f):
yield idx, json.load(row)
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