Datasets:

clips
/

mfaq

	# 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(
	{
	"domain_id": datasets.Value("int64"),
	"pair_id": datasets.Value("int64"),
	"language": datasets.Value("string"),
	"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}", {
	"domain_id": data["id"],
	"pair_id": i,
	"domain": data["domain"],
	"language": data["language"],
	"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"]
	}