Datasets:
Tasks:
Question Answering
Modalities:
Text
Sub-tasks:
closed-domain-qa
Languages:
English
Size:
1K - 10K
ArXiv:
License:
updated to dataset v 0.3 + added test split
Browse files
qasper.py
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# coding=utf-8
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# Copyright
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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@@ -38,10 +38,13 @@ A dataset containing 1585 papers with 5049 information-seeking questions asked b
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"""
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_HOMEPAGE = "https://allenai.org/data/qasper"
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_VERSION = "0.
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class Qasper(datasets.GeneratorBasedBuilder):
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),
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}
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),
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}
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)
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@@ -106,16 +115,28 @@ class Qasper(datasets.GeneratorBasedBuilder):
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)
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def _split_generators(self, dl_manager):
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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),
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={
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),
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]
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# coding=utf-8
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+
# Copyright 2022 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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"""
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_HOMEPAGE = "https://allenai.org/data/qasper"
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_URL_TRAIN_DEV = "https://qasper-dataset.s3.us-west-2.amazonaws.com/qasper-train-dev-v0.3.tgz"
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_URL_TEST = "https://qasper-dataset.s3.us-west-2.amazonaws.com/qasper-test-and-evaluator-v0.3.tgz"
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_DATA_FILES = {"train": "qasper-train-v0.3.json",
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"dev": "qasper-dev-v0.3.json",
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"test": "qasper-test-v0.3.json"}
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_VERSION = "0.3.0"
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class Qasper(datasets.GeneratorBasedBuilder):
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),
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}
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),
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"figures_and_tables": datasets.features.Sequence(
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{
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"caption": datasets.Value("string"),
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"file": datasets.Value("string"),
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}
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),
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}
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)
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)
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def _split_generators(self, dl_manager):
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archive_train_dev, archive_test = dl_manager.download((
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_URL_TRAIN_DEV, _URL_TEST)
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)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"filepath": _DATA_FILES["train"],
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"files": dl_manager.iter_archive(archive_train_dev)},
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),
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={
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"filepath": _DATA_FILES["dev"],
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"files": dl_manager.iter_archive(archive_train_dev)},
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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"filepath": _DATA_FILES["test"],
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"files": dl_manager.iter_archive(archive_test)},
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),
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]
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