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Upload korpus_nusantara.py with huggingface_hub
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korpus_nusantara.py
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from pathlib import Path
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from typing import List
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import re
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import datasets
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import pandas as pd
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from nusacrowd.utils import schemas
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from nusacrowd.utils.configs import NusantaraConfig
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from nusacrowd.utils.constants import Tasks, DEFAULT_SOURCE_VIEW_NAME, DEFAULT_NUSANTARA_VIEW_NAME
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_DATASETNAME = "korpus_nusantara"
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_SOURCE_VIEW_NAME = DEFAULT_SOURCE_VIEW_NAME
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_UNIFIED_VIEW_NAME = DEFAULT_NUSANTARA_VIEW_NAME
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_LANGUAGES = ["ind", "jav", "xdy", "bug", "sun", "mad", "bjn", "bbc", "khek", "msa", "min", "tiociu"] # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
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_LOCAL = False
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_CITATION = """\
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@article{sujaini2020improving,
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title={Improving the role of language model in statistical machine translation (Indonesian-Javanese)},
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author={Sujaini, Herry},
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journal={International Journal of Electrical and Computer Engineering},
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volume={10},
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number={2},
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pages={2102},
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year={2020},
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publisher={IAES Institute of Advanced Engineering and Science}
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}
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"""
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+
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_DESCRIPTION = """\
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This parallel corpus was collected from several studies, assignments, and thesis of
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students of the Informatics Study Program, Tanjungpura University. Some of the corpus
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34 |
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are used in the translation machine from Indonesian to local languages http://nustor.untan.ac.id/cammane/.
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This corpus can be used freely for research purposes by citing the paper
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https://ijece.iaescore.com/index.php/IJECE/article/download/20046/13738.
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+
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+
The dataset is a combination of multiple machine translation works from the author,
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Herry Sujaini, covering Indonesian to 25 local dialects in Indonesia. Since not all
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dialects have ISO639-3 standard coding, as agreed with Pak Herry , we decided to
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group the dataset into the closest language family, i.e.: Javanese, Dayak, Buginese,
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42 |
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Sundanese, Madurese, Banjar, Batak Toba, Khek, Malay, Minangkabau, and Tiociu.
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"""
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+
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_HOMEPAGE = "https://github.com/herrysujaini/korpusnusantara"
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_LICENSE = "Unknown"
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_URLS = {
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_DATASETNAME: "https://github.com/herrysujaini/korpusnusantara/raw/main/korpus nusantara.xlsx",
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+
}
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_SUPPORTED_TASKS = [Tasks.MACHINE_TRANSLATION]
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+
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_SOURCE_VERSION = "1.0.0"
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_NUSANTARA_VERSION = "1.0.0"
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+
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+
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"""
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A collection of all the dialects are: javanese, javanese kromo, javanese ngoko, dayak ahe,
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dayak iban, dayak pesaguan, dayak taman, buginese kelolau, buginese wajo, sundanese,
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59 |
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madurese, banjar, batak toba, khek pontianak, kapuas hulu, melayu kembayan, melayu ketapang,
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melayu melawi, melayu pontianak, melayu putussibau, melayu sambas, melayu sintang, padang,
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tiociu pontianak.
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+
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In this project, we group the dialects into several subsets:
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Javanese (jav) : javanese, javanese kromo, javanese ngoko
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+
Dayak (day) : dayak ahe, dayak iban, dayak pesaguan, dayak taman
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+
Buginese (bug) : buginese kelolau, buginese wajo
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+
Sundanese (sun) : sundanese
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+
Madurese (mad) : madurese
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+
Banjar (bjn) : banjar
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+
Batak Toba (bbc) : batak toba
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+
Khek (khek) : khek pontianak, kapuas hulu
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+
Malay (msa) : melayu kembayan, melayu ketapang, melayu melawi, melayu pontianak, melayu putussibau, melayu sambas, melayu sintang
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Minangkabau (min): padang
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Tiociu (tiociu) : tiociu pontianak
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"""
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Domain2Subsets = {
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"jav": ['jawa', 'jawa kromo', 'jawa ngoko'],
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"xdy": ['dayak ahe', 'dayak iban', 'dayak pesaguan', 'dayak taman'],
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"bug": ['bugis kelolao', 'bugis wajo'],
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"sun": ['sunda'],
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"mad": ['madura'],
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"bjn": ['banjar'],
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"bbc": ['Batak'],
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"khek": ['kapuas hulu', 'Khek Pontianak'],
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"msa": ['melayu kembayan', 'melayu ketapang', 'melayu melawi', 'melayu pontianak', 'melayu putussibau', 'melayu sambas', 'melayu sintang'],
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"min": ['padang'],
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"tiociu": ['Tiociu Pontianak'],
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}
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+
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class KorpusNusantara(datasets.GeneratorBasedBuilder):
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"""Bible En-Id is a machine translation dataset containing Indonesian-English parallel sentences collected from the bible.."""
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+
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BUILDER_CONFIGS = [
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NusantaraConfig(
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name=f"korpus_nusantara_ind_{subset}_source",
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version=datasets.Version(_SOURCE_VERSION),
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description=f"Korpus_Nusantara ind2{subset} source schema",
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schema="source",
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subset_id=f"korpus_nusantara",
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)
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for subset in _LANGUAGES[1:]
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] + \
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[
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+
NusantaraConfig(
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name=f"korpus_nusantara_ind_{subset}_nusantara_t2t",
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version=datasets.Version(_NUSANTARA_VERSION),
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description=f"Korpus_Nusantara ind2{subset} Nusantara schema",
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schema="nusantara_t2t",
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subset_id=f"korpus_nusantara",
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)
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for subset in _LANGUAGES[1:]
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] + \
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[
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+
NusantaraConfig(
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name=f"korpus_nusantara_{subset}_ind_source",
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version=datasets.Version(_SOURCE_VERSION),
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description=f"Korpus_Nusantara {subset}2ind source schema",
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schema="source",
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subset_id=f"korpus_nusantara",
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)
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for subset in _LANGUAGES[1:]
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] + \
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[
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+
NusantaraConfig(
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name=f"korpus_nusantara_{subset}_ind_nusantara_t2t",
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+
version=datasets.Version(_NUSANTARA_VERSION),
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+
description=f"Korpus_Nusantara {subset}2ind Nusantara schema",
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schema="nusantara_t2t",
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subset_id=f"korpus_nusantara",
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)
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for subset in _LANGUAGES[1:]
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+
]
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+
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DEFAULT_CONFIG_NAME = "korpus_nusantara_jav_ind_source"
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+
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def _info(self):
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if self.config.schema == "source":
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features = datasets.Features({"id": datasets.Value("string"), "text": datasets.Value("string"), "label": datasets.Value("string")})
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+
elif self.config.schema == "nusantara_t2t":
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features = schemas.text2text_features
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+
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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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148 |
+
license=_LICENSE,
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citation=_CITATION,
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+
)
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+
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+
def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
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"""Returns SplitGenerators."""
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# Dataset does not have predetermined split, putting all as TRAIN
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urls = _URLS[_DATASETNAME]
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+
base_dir = Path(dl_manager.download(urls))
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data_files = {"train": base_dir}
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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": data_files["train"],
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+
},
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),
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+
]
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+
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+
def _merge_subsets(self, dfs, subsets, revert=False):
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if not subsets: return None
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df = None
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+
for subset in subsets:
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sub_df = dfs[subset]
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orig_columns = sub_df.columns.tolist()
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sub_df.columns = ["label", "text"]+orig_columns[2:] if revert else ["text", "label"]+orig_columns[2:]
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+
if df is None:
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df = sub_df
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else:
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df = pd.concat([df, sub_df], axis=0, sort=False)
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return df
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+
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def get_domain_data(self, dfs):
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domain = self.config.name
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matched_domain = re.findall(r"korpus_nusantara_.*?_.*?_", domain)
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184 |
+
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assert len(matched_domain) == 1
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domain = matched_domain[0][:-1].replace("korpus_nusantara_", "").split("_")
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src_lang, tgt_lang = domain[0], domain[1]
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+
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subsets = Domain2Subsets.get(src_lang if src_lang != "ind" else tgt_lang, None)
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return src_lang, tgt_lang, self._merge_subsets(dfs, subsets, revert=(src_lang != "ind"))
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+
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+
def _generate_examples(self, filepath: Path):
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+
"""Yields examples as (key, example) tuples."""
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+
dfs = pd.read_excel(filepath, sheet_name=None, header=None)
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+
src_lang, tgt_lang, df = self.get_domain_data((dfs))
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196 |
+
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197 |
+
if self.config.schema == "source":
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198 |
+
for idx, row in enumerate(df.itertuples()):
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+
ex = {
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200 |
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"id": str(idx),
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"text": row.text,
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+
"label": row.label,
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+
}
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yield idx, ex
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+
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+
elif self.config.schema == "nusantara_t2t":
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for idx, row in enumerate(df.itertuples()):
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+
ex = {
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"id": str(idx),
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+
"text_1": row.text,
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+
"text_2": row.label,
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212 |
+
"text_1_name": src_lang,
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+
"text_2_name": tgt_lang,
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+
}
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+
yield idx, ex
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+
else:
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+
raise ValueError(f"Invalid config: {self.config.name}")
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