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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.
import csv
import json
import os
import datasets
_CITATION = """\
@InProceedings{mfaq_a_multilingual_dataset,
title={MFAQ: a Multilingual FAQ Dataset},
author={Maxime {De Bruyn} and Ehsan Lotfi and Jeska Buhmann and Walter Daelemans},
year={2021},
booktitle={MRQA @ EMNLP 2021}
}
"""
_DESCRIPTION = """\
We present the first multilingual FAQ dataset publicly available. We collected around 6M FAQ pairs from the web, in 21 different languages.
"""
_HOMEPAGE = ""
_LICENSE = ""
_LANGUAGES = ["cs", "da", "de", "en", "es", "fi", "fr", "he", "hr", "hu", "id", "it", "nl", "no", "pl", "pt", "ro", "ru", "sv", "tr", "vi"]
_URLs = {}
_URLs.update({f"{l}": {"train": [f"data/{l}/train.jsonl"], "valid": [f"data/{l}/valid.jsonl"]} for l in _LANGUAGES})
_URLs["all"] = {"train": [f"data/{l}/train.jsonl" for l in _LANGUAGES], "valid": [f"data/{l}/valid.jsonl" for l in _LANGUAGES]}
_URLs.update({f"{l}_flat": {"train": [f"data/{l}/train.jsonl"], "valid": [f"data/{l}/valid.jsonl"]} for l in _LANGUAGES})
_URLs["all_flat"] = {"train": [f"data/{l}/train.jsonl" for l in _LANGUAGES], "valid": [f"data/{l}/valid.jsonl" for l in _LANGUAGES]}
class MFAQ(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = list(map(lambda x: datasets.BuilderConfig(name=x, version=datasets.Version("1.1.0")), _URLs.keys()))
DEFAULT_CONFIG_NAME = "all"
def _info(self):
if "_flat" in self.config.name:
features = datasets.Features(
{
"id": datasets.Value("int64"),
"language": datasets.Value("string"),
"num_pairs": datasets.Value("int64"),
"domain": datasets.Value("string"),
"question": datasets.Value("string"),
"answer": datasets.Value("string")
}
)
else:
features = datasets.Features(
{
"id": datasets.Value("int64"),
"language": datasets.Value("string"),
"num_pairs": datasets.Value("int64"),
"domain": datasets.Value("string"),
"qa_pairs": [
{
"question": datasets.Value("string"),
"answer": datasets.Value("string"),
"language": datasets.Value("string")
}
]
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features, # Here we define them above because they are different between the two configurations
supervised_keys=None,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
my_urls = _URLs[self.config.name]
data_dir = dl_manager.download_and_extract(my_urls)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"filepaths": data_dir["train"], "split": "train"},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={"filepaths": data_dir["valid"], "split": "valid"},
),
]
def _generate_examples(
self, filepaths, split # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
):
""" Yields examples as (key, example) tuples. """
for filepath in filepaths:
with open(filepath, encoding="utf-8") as f:
for _id, row in enumerate(f):
data = json.loads(row)
if "flat" in self.config.name:
for i, pair in enumerate(data["qa_pairs"]):
yield f"{filepath}_{_id}_{i}", {
"id": data["id"],
"domain": data["domain"],
"language": data["language"],
"num_pairs": 1,
"question": pair["question"],
"answer": pair["answer"]
}
else:
yield f"{filepath}_{_id}", {
"id": data["id"],
"domain": data["domain"],
"language": data["language"],
"num_pairs": data["num_pairs"],
"qa_pairs": data["qa_pairs"]
}
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