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import os | ||
from pathlib import Path | ||
from typing import Dict, List, Tuple | ||
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import datasets | ||
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from nusantara.utils.configs import NusantaraConfig | ||
from nusantara.utils.constants import Tasks | ||
from nusantara.utils import schemas | ||
import json | ||
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_CITATION = """\ | ||
https://quoradata.quora.com/First-Quora-Dataset-Release-Question-Pairs | ||
""" | ||
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_DATASETNAME = "id_qqp" | ||
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_DESCRIPTION = """\ | ||
INDOSUM is a new benchmark dataset for Indonesian text summarization. | ||
The dataset consists of news articles and manually constructed summaries. | ||
""" | ||
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_HOMEPAGE = "https://github.com/louisowen6/quora_paraphrasing_id" | ||
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_LICENSE = "Apache License, Version 2.0" | ||
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_URLS = { | ||
_DATASETNAME: [ | ||
"https://github.com/louisowen6/quora_paraphrasing_id/raw/main/ID_Quora_Paraphrasing_train.json", | ||
"https://github.com/louisowen6/quora_paraphrasing_id/raw/main/ID_Quora_Paraphrasing_val.json", | ||
] | ||
} | ||
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_SUPPORTED_TASKS = [Tasks.PARAPHRASING] | ||
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_SOURCE_VERSION = "1.0.0" | ||
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_NUSANTARA_VERSION = "1.0.0" | ||
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class IndoSUM(datasets.GeneratorBasedBuilder): | ||
"""INDOSUM is a new benchmark dataset for Indonesian text summarization. The dataset consists of news articles and manually constructed summaries.""" | ||
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SOURCE_VERSION = datasets.Version(_SOURCE_VERSION) | ||
NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION) | ||
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BUILDER_CONFIGS = [ | ||
NusantaraConfig( | ||
name="id_qqp_source", | ||
version=SOURCE_VERSION, | ||
description="ID QQP source schema", | ||
schema="source", | ||
subset_id="id_qqp", | ||
), | ||
NusantaraConfig( | ||
name="id_qqp_nusantara_t2t", | ||
version=NUSANTARA_VERSION, | ||
description="ID QQP Nusantara schema", | ||
schema="nusantara_t2t", | ||
subset_id="id_qqp", | ||
), | ||
] | ||
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DEFAULT_CONFIG_NAME = "id_qqp_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( | ||
{ | ||
"id": datasets.Value("string"), | ||
"question_1": datasets.Value("string"), | ||
"question_2": datasets.Value("string") | ||
} | ||
) | ||
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elif self.config.schema == "nusantara_t2t": | ||
features = schemas.text2text_features | ||
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return datasets.DatasetInfo( | ||
description=_DESCRIPTION, | ||
features=features, | ||
homepage=_HOMEPAGE, | ||
license=_LICENSE, | ||
citation=_CITATION, | ||
) | ||
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def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: | ||
urls = _URLS[_DATASETNAME] | ||
data_dir = dl_manager.download_and_extract(urls) | ||
return [ | ||
datasets.SplitGenerator( | ||
name=datasets.Split.TRAIN, | ||
gen_kwargs={ | ||
"filepath": data_dir[0], | ||
}, | ||
), | ||
datasets.SplitGenerator( | ||
name=datasets.Split.VALIDATION, | ||
gen_kwargs={ | ||
"filepath": data_dir[1], | ||
}, | ||
), | ||
] | ||
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def _generate_examples(self, filepath: Path) -> Tuple[int, Dict]: | ||
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with open(filepath, "r") as f: | ||
lines = f.readlines() | ||
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if self.config.schema == "source": | ||
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for i, line in enumerate(lines): | ||
line = json.loads(line.strip()) | ||
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sample = { | ||
"id": str(i), | ||
"question_1": line["question_1"], | ||
"question_2": line["question_2"] | ||
} | ||
yield i, sample | ||
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elif self.config.schema == "nusantara_t2t": | ||
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for i, line in enumerate(lines): | ||
line = json.loads(line.strip()) | ||
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sample = { | ||
"id": str(i), | ||
"text_1": line["question_1"], | ||
"text_2": line["question_2"], | ||
"text_1_name": "question_1", | ||
"text_2_name": "question_2" | ||
} | ||
yield i, sample |