Init commit with basic data loader
Browse files
bisect.py
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# coding=utf-8
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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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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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"""BiSECT is a Split and Rephrase corpus created via bilingual pivoting."""
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import os
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import datasets
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_CITATION = """\
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@inproceedings{kim-etal-2021-bisect,
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title = "{B}i{SECT}: Learning to Split and Rephrase Sentences with Bitexts",
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author = "Kim, Joongwon and
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Maddela, Mounica and
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Kriz, Reno and
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Xu, Wei and
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Callison-Burch, Chris",
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booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
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month = nov,
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year = "2021",
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address = "Online and Punta Cana, Dominican Republic",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2021.emnlp-main.500",
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pages = "6193--6209"
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}
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"""
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_DESCRIPTION = """\
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BiSECT is a Split and Rephrase corpus created via bilingual pivoting.
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"""
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_HOMEPAGE = "https://github.com/mounicam/BiSECT"
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_URL = "https://github.com/mounicam/BiSECT/raw/main/bisect/"
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_URLs = {
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"train": {"src": _URL + "train.src.gz", "dst": _URL + "train.dst.gz"},
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"validation": {"src": _URL + "valid.src.gz", "dst": _URL + "valid.dst.gz"},
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"test": {"src": _URL + "test.src.gz", "dst": _URL + "test.dst.gz"},
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}
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class BiSECT(datasets.GeneratorBasedBuilder):
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"""The BiSECT Split and Rephrase corpus."""
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VERSION = datasets.Version("1.0.0")
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(
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name="bisect",
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version=VERSION,
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description="Data described in the BiSECT paper",
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)
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]
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DEFAULT_CONFIG_NAME = "bisect"
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def _info(self):
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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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"gem_id": datasets.Value("string"),
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"source_sentence": datasets.Value("string"),
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"target_sentence": datasets.Value("string"),
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}
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),
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supervised_keys=None,
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homepage=_HOMEPAGE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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data_dir = dl_manager.download_and_extract(_URLs)
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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={"filepath": data_dir["train"], "split": "train"},
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={"filepath": data_dir["test"], "split": "test"},
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),
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={"filepath": data_dir["validation"], "split": "validation"},
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),
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]
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def _generate_examples(self, filepath, split):
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"""Yields examples as (key, example) tuples."""
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source_filepath = filepath["src"]
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target_filepath = filepath["dst"]
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with open(source_filepath, encoding="utf-8") as f:
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source_lines = [line.strip() for line in f]
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with open(target_filepath, encoding="utf-8") as f:
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target_lines = [line.strip() for line in f]
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for id_ in range(len(source_lines)):
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yield id_, {
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"gem_id": f"{self.config.name}-{split}-{id_}",
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"source_sentence": source_lines[id_],
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"target_sentence": target_lines[id_],
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}
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