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talpco.py

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+import os
+from pathlib import Path
+from typing import Dict, List
+
+import datasets
+
+from nusacrowd.utils import schemas
+from nusacrowd.utils.configs import NusantaraConfig
+from nusacrowd.utils.constants import Tasks
+
+_CITATION = """\
+@article{published_papers/22434604,
+  title = {TUFS Asian Language Parallel Corpus (TALPCo)},
+  author = {Hiroki Nomoto and Kenji Okano and David Moeljadi and Hideo Sawada},
+  journal = {言語処理学会 第24回年次大会 発表論文集},
+  pages = {436--439},
+  year = {2018}
+}
+@article{published_papers/22434603,
+  title = {Interpersonal meaning annotation for Asian language corpora: The case of TUFS Asian Language Parallel Corpus (TALPCo)},
+  author = {Hiroki Nomoto and Kenji Okano and Sunisa Wittayapanyanon and Junta Nomura},
+  journal = {言語処理学会 第25回年次大会 発表論文集},
+  pages = {846--849},
+  year = {2019}
+}
+"""
+_DATASETNAME = "talpco"
+_DESCRIPTION = """\
+The TUFS Asian Language Parallel Corpus (TALPCo) is an open parallel corpus consisting of Japanese sentences
+and their translations into Korean, Burmese (Myanmar; the official language of the Republic of the Union of Myanmar),
+Malay (the national language of Malaysia, Singapore and Brunei), Indonesian, Thai, Vietnamese and English.
+"""
+_HOMEPAGE = "https://github.com/matbahasa/TALPCo"
+_LOCAL = False
+_LANGUAGES = ["eng", "ind", "jpn", "kor", "myn", "tha", "vie", "zsm"]
+_LICENSE = "CC-BY 4.0"
+_URLS = {
+    _DATASETNAME: "https://github.com/matbahasa/TALPCo/archive/refs/heads/master.zip",
+}
+_SUPPORTED_TASKS = [Tasks.MACHINE_TRANSLATION]
+_SOURCE_VERSION = "1.0.0"
+_NUSANTARA_VERSION = "1.0.0"
+
+
+def nusantara_config_constructor(lang_source, lang_target, schema, version):
+    """Construct NusantaraConfig with talpco_{lang_source}_{lang_target}_{schema} as the name format"""
+    if schema != "source" and schema != "nusantara_t2t":
+        raise ValueError(f"Invalid schema: {schema}")
+
+    if lang_source == "" and lang_target == "":
+        return NusantaraConfig(
+            name="talpco_{schema}".format(schema=schema),
+            version=datasets.Version(version),
+            description="talpco with {schema} schema for all 7 language pairs from / to ind language".format(schema=schema),
+            schema=schema,
+            subset_id="talpco",
+        )
+    else:
+        return NusantaraConfig(
+            name="talpco_{lang_source}_{lang_target}_{schema}".format(lang_source=lang_source, lang_target=lang_target, schema=schema),
+            version=datasets.Version(version),
+            description="talpco with {schema} schema for {lang_source} source language and  {lang_target} target language".format(lang_source=lang_source, lang_target=lang_target, schema=schema),
+            schema=schema,
+            subset_id="talpco",
+        )
+
+
+class TALPCo(datasets.GeneratorBasedBuilder):
+    """TALPCo datasets contains 1372 datasets in 8 languages"""
+
+    BUILDER_CONFIGS = (
+        [nusantara_config_constructor(lang1, lang2, "source", _SOURCE_VERSION) for lang1 in _LANGUAGES for lang2 in _LANGUAGES if lang1 != lang2]
+        + [nusantara_config_constructor(lang1, lang2, "nusantara_t2t", _NUSANTARA_VERSION) for lang1 in _LANGUAGES for lang2 in _LANGUAGES if lang1 != lang2]
+        + [nusantara_config_constructor("", "", "source", _SOURCE_VERSION), nusantara_config_constructor("", "", "nusantara_t2t", _NUSANTARA_VERSION)]
+    )
+
+    DEFAULT_CONFIG_NAME = "talpco_jpn_ind_source"
+
+    def _info(self) -> datasets.DatasetInfo:
+        if self.config.schema == "source" or self.config.schema == "nusantara_t2t":
+            features = schemas.text2text_features
+        else:
+            raise ValueError(f"Invalid config schema: {self.config.schema}")
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        urls = _URLS[_DATASETNAME]
+        base_path = Path(dl_manager.download_and_extract(urls)) / "TALPCo-master"
+        data = {}
+        for lang in _LANGUAGES:
+            lang_file_name = "data_" + lang + ".txt"
+            lang_file_path = base_path / lang / lang_file_name
+            if os.path.isfile(lang_file_path):
+                with open(lang_file_path, "r") as file:
+                    data[lang] = file.read().strip("\n").split("\n")
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "data": data,
+                    "split": "train",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, data: Dict, split: str):
+        if self.config.schema != "source" and self.config.schema != "nusantara_t2t":
+            raise ValueError(f"Invalid config schema: {self.config.schema}")
+
+        if self.config.name == "talpco_source" or self.config.name == "talpco_nusantara_t2t":
+            # load all 7 language pairs from / to ind language
+            lang_target = "ind"
+            for lang_source in _LANGUAGES:
+                if lang_source == lang_target:
+                    continue
+                for language_pair_data in self.generate_language_pair_data(lang_source, lang_target, data):
+                    yield language_pair_data
+
+            lang_source = "ind"
+            for lang_target in _LANGUAGES:
+                if lang_source == lang_target:
+                    continue
+                for language_pair_data in self.generate_language_pair_data(lang_source, lang_target, data):
+                    yield language_pair_data
+        else:
+            _, lang_source, lang_target = self.config.name.replace(f"_{self.config.schema}", "").split("_")
+            for language_pair_data in self.generate_language_pair_data(lang_source, lang_target, data):
+                yield language_pair_data
+
+    def generate_language_pair_data(self, lang_source, lang_target, data):
+        dict_source = {}
+        for row in data[lang_source]:
+            id, text = row.split("\t")
+            dict_source[id] = text
+
+        dict_target = {}
+        for row in data[lang_target]:
+            id, text = row.split("\t")
+            dict_target[id] = text
+
+        all_ids = set([k for k in dict_source.keys()] + [k for k in dict_target.keys()])
+        dict_merged = {k: [dict_source.get(k), dict_target.get(k)] for k in all_ids}
+
+        for id in sorted(all_ids):
+            ex = {
+                "id": lang_source + "_"  + lang_target + "_"  + id,
+                "text_1": dict_merged[id][0],
+                "text_2": dict_merged[id][1],
+                "text_1_name": lang_source,
+                "text_2_name": lang_target,
+            }
+            yield lang_source + "_" + lang_target + "_"  + id, ex