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import os |
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from pathlib import Path |
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from typing import Dict, List, Tuple |
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import datasets |
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from nusacrowd.utils.configs import NusantaraConfig |
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from nusacrowd.utils.constants import Tasks |
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from nusacrowd.utils import schemas |
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import jsonlines |
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from nltk.tokenize.treebank import TreebankWordDetokenizer |
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_CITATION = """\ |
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@inproceedings{hasan2021xl, |
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title={XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages}, |
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author={Hasan, Tahmid and Bhattacharjee, Abhik and Islam, Md Saiful and Mubasshir, Kazi and Li, Yuan-Fang and Kang, Yong-Bin and Rahman, M Sohel and Shahriyar, Rifat}, |
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booktitle={Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021}, |
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pages={4693--4703}, |
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year={2021} |
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} |
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""" |
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_LOCAL = False |
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_LANGUAGES = ["ind", "eng"] |
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_DATASETNAME = "xl_sum" |
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_DESCRIPTION = """\ |
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XL-Sum is a large-scale multilingual summarization dataset that covers 45 languages including Indonesian text summarization. |
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The dataset is based on article-summary pairs from BBC, is highly abstractive, concise, and of high quality, as indicated by human and intrinsic evaluation. |
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""" |
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_HOMEPAGE = "https://github.com/csebuetnlp/xl-sum" |
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_LICENSE = "CC-BY-NC-SA 4.0" |
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_URLS = { |
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_DATASETNAME: "https://huggingface.co/datasets/csebuetnlp/xlsum/resolve/main/data/indonesian_XLSum_v2.0.tar.bz2", |
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} |
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_SUPPORTED_TASKS = [Tasks.SUMMARIZATION] |
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_SOURCE_VERSION = "2.0.0" |
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_NUSANTARA_VERSION = "1.0.0" |
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class XLSum(datasets.GeneratorBasedBuilder): |
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"""XL-Sum is a large-scale multilingual summarization dataset that covers 45 languages including Indonesian text summarization. The dataset is based on article-summary pairs from BBC, is highly abstractive, concise, and of high quality, as indicated by human and intrinsic evaluation.""" |
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SOURCE_VERSION = datasets.Version(_SOURCE_VERSION) |
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NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION) |
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BUILDER_CONFIGS = [ |
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NusantaraConfig( |
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name="xl_sum_source", |
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version=datasets.Version(_SOURCE_VERSION), |
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description="xl_sum source schema", |
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schema="source", |
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subset_id="xl_sum", |
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), |
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NusantaraConfig( |
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name="xl_sum_nusantara_t2t", |
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version=datasets.Version(_NUSANTARA_VERSION), |
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description="xl_sum Nusantara schema", |
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schema="nusantara_t2t", |
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subset_id="xl_sum", |
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), |
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] |
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DEFAULT_CONFIG_NAME = "xl_sum_source" |
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def _info(self) -> datasets.DatasetInfo: |
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if self.config.schema == "source": |
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features = datasets.Features( |
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{ |
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"id": datasets.Value("string"), |
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"url": datasets.Value("string"), |
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"title": datasets.Value("string"), |
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"text": datasets.Value("string"), |
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"summary": datasets.Value("string") |
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} |
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) |
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elif self.config.schema == "nusantara_t2t": |
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features = schemas.text2text_features |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: |
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data_dir = Path(dl_manager.download_and_extract(_URLS[_DATASETNAME])) |
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data_files = { |
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"train": "indonesian_train.jsonl", |
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"validation": "indonesian_val.jsonl", |
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"test": "indonesian_test.jsonl", |
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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": os.path.join(data_dir, data_files["train"]), |
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"split": "train", |
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}, |
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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": os.path.join(data_dir, data_files["validation"]), |
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"split": "dev", |
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}, |
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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": os.path.join(data_dir, data_files["test"]), |
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"split": "test", |
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}, |
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), |
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] |
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def _generate_examples(self, filepath: Path, split: str) -> Tuple[int, Dict]: |
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if self.config.schema == "source": |
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with jsonlines.open(filepath) as f: |
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for each_data in f.iter(): |
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ex = { |
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"id": each_data["id"], |
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"url": each_data["url"], |
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"title": each_data["title"], |
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"text": each_data["text"], |
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"summary": each_data["summary"], |
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} |
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yield each_data["id"], ex |
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elif self.config.schema == "nusantara_t2t": |
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with jsonlines.open(filepath) as f: |
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for each_data in f.iter(): |
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ex = { |
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"id": each_data["id"], |
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"text_1": each_data["text"], |
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"text_2": each_data["summary"], |
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"text_1_name": each_data["title"], |
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"text_2_name": "summary" |
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} |
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yield each_data["id"], ex |
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else: |
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raise ValueError(f"Invalid config: {self.config.name}") |
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