Datasets:

Tevatron
/

xor-tydi

Tags:

Dataset card Viewer Files Files and versions Community

xor-tydi / xor-tydi.py

Xinyu Crystina ZHANG

url

92d883f over 1 year ago

raw history blame contribute delete

No virus

5.35 kB

	# 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.

	# Lint as: python3
	"""Wikipedia NQ dataset."""

	import json

	import datasets

	_CITATION = """
	@inproceedings{xorqa,
	title = {{XOR} {QA}: Cross-lingual Open-Retrieval Question Answering},
	author = {Akari Asai and Jungo Kasai and Jonathan H. Clark and Kenton Lee and Eunsol Choi and Hannaneh Hajishirzi},
	booktitle={NAACL-HLT},
	year = {2021}
	}
	"""

	_DESCRIPTION = "dataset load script for Wikipedia NQ"

	base = "/home/czhang/src/task-sparse/tevatron/hgf_datasets/xor-tydi"
	_DATASET_URLS = {
	'eng_span': {
	'train': f'https://huggingface.co/datasets/Tevatron/xor-tydi/resolve/main/train/xor-t2e-100w.jsonl.gz',
	'dev': f'https://huggingface.co/datasets/Tevatron/xor-tydi/resolve/main/dev/xor_dev_retrieve_eng_span_v1_1.jsonl',
	'test': f'https://huggingface.co/datasets/Tevatron/xor-tydi/resolve/main/test/xor_test_retrieve_eng_span_q_only_v1_1.jsonl',
	},
	'full': {
	'train': f'https://huggingface.co/datasets/Tevatron/xor-tydi/resolve/main/train/xor-t2e-100w.jsonl.gz',
	'dev': f'https://huggingface.co/datasets/Tevatron/xor-tydi/resolve/main/dev/xor_dev_full_v1_1.jsonl',
	'test': f'https://huggingface.co/datasets/Tevatron/xor-tydi/resolve/main/test/xor_test_full_q_only_v1_1.jsonl',
	}
	# 'test': f"{base}",
	}


	class XORTyDi(datasets.GeneratorBasedBuilder):
	VERSION = datasets.Version("0.0.1")

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(
	version=VERSION,
	name="eng_span",
	description="XOR-TyDI train/dev/test datasets of English Span Task"),
	datasets.BuilderConfig(
	version=VERSION,
	name="full",
	description="XOR-TyDI train/dev/test datasets of Full Task"),
	]

	def _info(self):
	features = datasets.Features({
	'query_id': datasets.Value('string'),
	'query': datasets.Value('string'),
	'answers': [datasets.Value('string')],
	'positive_passages': [
	{'docid': datasets.Value('string'), 'text': datasets.Value('string'),
	'title': datasets.Value('string')}
	],
	'negative_passages': [
	{'docid': datasets.Value('string'), 'text': datasets.Value('string'),
	'title': datasets.Value('string')}
	],
	})
	return datasets.DatasetInfo(
	# This is the description that will appear on the datasets page.
	description=_DESCRIPTION,
	# This defines the different columns of the dataset and their types
	features=features, # Here we define them above because they are different between the two configurations
	supervised_keys=None,
	# Homepage of the dataset for documentation
	homepage="",
	# License for the dataset if available
	license="",
	# Citation for the dataset
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	group = self.config.name
	if self.config.data_files:
	downloaded_files = self.config.data_files
	else:
	downloaded_files = dl_manager.download_and_extract(_DATASET_URLS[group])
	splits = [
	datasets.SplitGenerator(
	name=split,
	gen_kwargs={
	"files": [downloaded_files[split]] if isinstance(downloaded_files[split], str) else downloaded_files[split],
	},
	) for split in downloaded_files
	]
	return splits

	def _generate_examples(self, files):
	"""Yields examples."""
	def process_train_entry(data):
	if data.get('negative_passages') is None:
	data['negative_passages'] = []
	if data.get('positive_passages') is None:
	data['positive_passages'] = []
	if data.get('answers') is None:
	data['answers'] = []
	return data['query_id'], data

	def process_dev_test_entry(data):
	return data["id"], {
	"query_id": data["id"],
	"query": data["question"],
	"answers": data.get("answers", []),
	"positive_passages": [],
	"negative_passages": [],
	}

	for filepath in files:
	with open(filepath, encoding="utf-8") as f:
	for line in f:
	data = json.loads(line)

	if "id" in data and "query_id" not in data:
	yield process_dev_test_entry(data)
	else:
	yield process_train_entry(data)