sc2qa commited on
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Files changed (4) hide show
  1. sc2q_commoncrawl_large.py +99 -0
  2. test.csv +3 -0
  3. train.csv +3 -0
  4. val.csv +3 -0
sc2q_commoncrawl_large.py ADDED
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+ # coding=utf-8
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+ # Copyright 2020 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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+ # You may obtain a copy of the License at
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+ #
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+ # http://www.apache.org/licenses/LICENSE-2.0
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+ #
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+ # Unless required by applicable law or agreed to in writing, software
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+ # distributed under the License is distributed on an "AS IS" BASIS,
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+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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+ # See the License for the specific language governing permissions and
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+ # limitations under the License.
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+
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+ # Lint as: python3
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+ """(SC)^2QA: Self-Contained Summary-Centric QA Dataset.
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+ This dataset (https://huggingface.co/datasets/sc2qa/sc2q_commoncrawl_large) contains 529,039 question and article pairs.
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+ If you want {Question, Article, Summary, Length Constraint} 4-tuples, please load sc2qa_commoncrawl (https://huggingface.co/datasets/sc2qa/sc2qa_commoncrawl)
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+ """
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+
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+ import csv
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+
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+ import datasets
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+
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+
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+ logger = datasets.logging.get_logger(__name__)
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+
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+
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+ _CITATION = """\
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+ @article{zhou2021generating,
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+ author = {Li Zhou, Kevin Small, Yong Zhang, Sandeep Atluri},
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+ title = "{Generating Self-Contained and Summary-Centric Question Answer Pairs via Differentiable Reward Imitation Learning}",
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+ conference = {The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021)},
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+ year = 2021,
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+ }
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+ """
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+
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+ _DESCRIPTION = """\
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+ """
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+
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+ _URLS = {
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+ "train":"https://huggingface.co/datasets/sc2qa/sc2q_commoncrawl/resolve/main/train.csv",
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+ "val":"https://huggingface.co/datasets/sc2qa/sc2q_commoncrawl/resolve/main/val.csv",
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+ "test":"https://huggingface.co/datasets/sc2qa/sc2q_commoncrawl/resolve/main/test.csv",
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+ }
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+
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+ class SC2QAConfig(datasets.BuilderConfig):
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+ """BuilderConfig for (SC)^2QA."""
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+
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+ def __init__(self, **kwargs):
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+ """BuilderConfig for (SC)^2QA.
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+
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+ Args:
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+ **kwargs: keyword arguments forwarded to super.
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+ """
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+ super(SC2QAConfig, self).__init__(**kwargs)
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+
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+
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+ class SC2QA(datasets.GeneratorBasedBuilder):
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+ BUILDER_CONFIGS = [
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+ SC2QAConfig(
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+ name="plain_text",
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+ version=datasets.Version("1.0.0", ""),
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+ description="Plain text",
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+ ),
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+ ]
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+
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+ def _info(self):
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+ # Should return a datasets.DatasetInfo object
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+ return datasets.DatasetInfo(
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+ description=_DESCRIPTION,
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+ features=datasets.Features(
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+ {
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+ "question": datasets.Value("string"),
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+ "article": datasets.Value("string"),
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+ "url": datasets.Value("string"),
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+ }
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+ ),
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+ citation=_CITATION,
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+ )
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+
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+ def _split_generators(self, dl_manager):
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+ downloaded_files = dl_manager.download_and_extract(_URLS)
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+
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+ return [
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+ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
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+ datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["val"]}),
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+ datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
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+ ]
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+
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+ def _generate_examples(self, filepath):
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+ """This function returns the examples in the raw (text) form."""
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+ logger.info("generating examples from = %s", filepath)
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+ key = 0
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+ with open(filepath, encoding="ascii", errors='ignore') as f:
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+ csv_reader = csv.DictReader(f)
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+ for i, row in enumerate(csv_reader):
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+ yield i, row
test.csv ADDED
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+ oid sha256:c67fd9e0170d188a9a6bb5a7e15a56ae2347a4ae4d9683f8aefedad508993cc8
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+ size 212319294
train.csv ADDED
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+ oid sha256:80624f565c91c646006a8d028dcc27021d5cbaa22e3d0be78f78be53d5815efb
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+ size 1886633620
val.csv ADDED
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+ size 108953981