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Closes SEACrowd#97 | Inter-Agency Task Force for the Management of Em…
…erging Infectious Diseases (IATF) COVID-19 Resolutions (SEACrowd#460)
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from pathlib import Path | ||
from typing import Dict, List, Tuple | ||
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import datasets | ||
import pyreadr | ||
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from seacrowd.utils import schemas | ||
from seacrowd.utils.configs import SEACrowdConfig | ||
from seacrowd.utils.constants import (TASK_TO_SCHEMA, Licenses, Tasks) | ||
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_DATASETNAME = "iatf" | ||
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_CITATION = """\ | ||
@misc{ | ||
iatf, | ||
title={Inter-Agency Task Force for the Management of Emerging Infectious Diseases (IATF) COVID-19 Resolutions}, | ||
url={https://como-ph.github.io/post/creating-text-data-from-iatf-resolutions/}, | ||
author={Chris Mercado, John Robert Medina, Ernest Guevarra} | ||
} | ||
""" | ||
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_DESCRIPTION = """\ | ||
To assess possible impact of various COVID-19 prediction models on Philippine government response, text from various resolutions issued by | ||
the Inter-agency Task Force for the Management of Emerging Infectious Diseases (IATF) has been collected using data mining approaches implemented in R. | ||
""" | ||
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_HOMEPAGE = "https://github.com/como-ph/covidphtext/tree/master/data" | ||
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_LICENSE = Licenses.GPL_3_0.value | ||
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_SUPPORTED_TASKS = [Tasks.SELF_SUPERVISED_PRETRAINING] | ||
_SEACROWD_SCHEMA_NAME = TASK_TO_SCHEMA[_SUPPORTED_TASKS[0]].lower() | ||
_LANGUAGES = ["fil"] | ||
_LOCAL = False | ||
_SOURCE_VERSION = "1.0.0" | ||
_SEACROWD_VERSION = "1.0.0" | ||
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_URL_BASE = "https://github.com/como-ph/covidphtext/raw/master/data/" | ||
_URLS = [ | ||
"iatfGuidelineOmnibus.rda", | ||
"iatfResolution01.rda", | ||
"iatfResolution02.rda", | ||
"iatfResolution03.rda", | ||
"iatfResolution04.rda", | ||
"iatfResolution05.rda", | ||
"iatfResolution06.rda", | ||
"iatfResolution07.rda", | ||
"iatfResolution08.rda", | ||
"iatfResolution09.rda", | ||
"iatfResolution10.rda", | ||
"iatfResolution11.rda", | ||
"iatfResolution12.rda", | ||
"iatfResolution13.rda", | ||
"iatfResolution14.rda", | ||
"iatfResolution15.rda", | ||
"iatfResolution16.rda", | ||
"iatfResolution17.rda", | ||
"iatfResolution18.rda", | ||
"iatfResolution19.rda", | ||
"iatfResolution20.rda", | ||
"iatfResolution21.rda", | ||
"iatfResolution22.rda", | ||
"iatfResolution23.rda", | ||
"iatfResolution24.rda", | ||
"iatfResolution25.rda", | ||
"iatfResolution26.rda", | ||
"iatfResolution27.rda", | ||
"iatfResolution28.rda", | ||
"iatfResolution29.rda", | ||
"iatfResolution30.rda", | ||
"iatfResolution30A.rda", | ||
"iatfResolution31.rda", | ||
"iatfResolution32.rda", | ||
"iatfResolution33.rda", | ||
"iatfResolution34.rda", | ||
"iatfResolution35.rda", | ||
"iatfResolution36.rda", | ||
"iatfResolution37.rda", | ||
"iatfResolution38.rda", | ||
"iatfResolution39.rda", | ||
"iatfResolution40.rda", | ||
"iatfResolution41.rda", | ||
"iatfResolution42.rda", | ||
"iatfResolution43.rda", | ||
"iatfResolution44.rda", | ||
"iatfResolution45.rda", | ||
"iatfResolution46.rda", | ||
"iatfResolution46A.rda", | ||
"iatfResolution47.rda", | ||
"iatfResolution48.rda", | ||
"iatfResolution49.rda", | ||
"iatfResolution50.rda", | ||
"iatfResolution50A.rda", | ||
"iatfResolution51.rda", | ||
"iatfResolution52.rda", | ||
"iatfResolution53.rda", | ||
"iatfResolution54.rda", | ||
"iatfResolution55.rda", | ||
"iatfResolution55A.rda", | ||
"iatfResolution56.rda", | ||
"iatfResolution57.rda", | ||
"iatfResolution58.rda", | ||
"iatfResolution59.rda", | ||
"iatfResolution60.rda", | ||
"iatfResolution60A.rda", | ||
] | ||
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class IATFDataset(datasets.GeneratorBasedBuilder): | ||
"""Inter-agency Task Force for the Management of Emerging Infectious Diseases Dataset""" | ||
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BUILDER_CONFIGS = [ | ||
SEACrowdConfig( | ||
name=f"{_DATASETNAME}_source", | ||
version=datasets.Version(_SOURCE_VERSION), | ||
description=f"{_DATASETNAME} source schema", | ||
schema="source", | ||
subset_id=f"{_DATASETNAME}", | ||
), | ||
SEACrowdConfig( | ||
name=f"{_DATASETNAME}_seacrowd_{_SEACROWD_SCHEMA_NAME}", | ||
version=datasets.Version(_SEACROWD_VERSION), | ||
description=f"{_DATASETNAME} seacrowd schema", | ||
schema=f"seacrowd_{_SEACROWD_SCHEMA_NAME}", | ||
subset_id=f"{_DATASETNAME}", | ||
), | ||
] | ||
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DEFAULT_CONFIG_NAME = f"{_DATASETNAME}_source" | ||
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def _info(self) -> datasets.DatasetInfo: | ||
if self.config.schema == "source": | ||
features = datasets.Features( | ||
{ | ||
"id": datasets.Value("string"), | ||
"text": datasets.Value("string"), | ||
} | ||
) | ||
elif self.config.schema == f"seacrowd_{_SEACROWD_SCHEMA_NAME}": | ||
features = schemas.self_supervised_pretraining.features | ||
else: | ||
raise ValueError(f"Invalid config schema: {self.config.schema}") | ||
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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]: | ||
filepaths = [Path(dl_manager.download(_URL_BASE + url)) for url in _URLS] | ||
return [ | ||
datasets.SplitGenerator( | ||
name=datasets.Split.TRAIN, | ||
gen_kwargs={"filepaths": filepaths}, | ||
), | ||
] | ||
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def _generate_examples(self, filepaths: List[Path]) -> Tuple[int, Dict]: | ||
counter = 0 | ||
for path in filepaths: | ||
data = pyreadr.read_r(path) | ||
text = " ".join([str(x) for x in data[list(data.keys())[0]]["text"].values]) | ||
if self.config.schema == "source": | ||
yield ( | ||
counter, | ||
{ | ||
"id": str(counter), | ||
"text": text.strip(), | ||
}, | ||
) | ||
elif self.config.schema == f"seacrowd_{_SEACROWD_SCHEMA_NAME}": | ||
yield ( | ||
counter, | ||
{ | ||
"id": str(counter), | ||
"text": text.strip(), | ||
}, | ||
) | ||
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counter += 1 |