Convert dataset to Parquet

README.md

@@ -15,7 +15,7 @@ dataset_info:
   - name: test
     num_bytes: 31035
     num_examples: 345
-  download_size: 24678400
+  download_size: 46450938
   dataset_size: 75673237
 - config_name: chv-rus
   features:
@@ -34,4 +34,12 @@ dataset_info:
     num_examples: 394
   download_size: 84889600
   dataset_size: 290881873
+configs:
+- config_name: chv-eng
+  data_files:
+  - split: train
+    path: chv-eng/train-*
+  - split: test
+    path: chv-eng/test-*
+  default: true
 ---

chv-eng/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f0880827c4d5ec66698ee497794a7539e8b81d1cdf96c6bc69bb3f6090ffe4f1
+size 20995

chv-eng/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d9f4dc86c62e7777975ae17592bec7edceeb7aee8f920ebd36a08b53a93796d2
+size 46429943

tatoeba-challenge.py

@@ -1,137 +0,0 @@
-import gzip
-from datasets import (
-    BuilderConfig,
-    GeneratorBasedBuilder,
-    DownloadManager,
-    StreamingDownloadManager,
-    Version,
-    SplitGenerator,
-    Split,
-    DatasetInfo,
-    Features,
-    Value,
-)
-from typing import Union
-from pathlib import Path
-
-
-class TatoebaChallengeConfig(BuilderConfig):
-    """Builder config for Tatoeba challenge dataset."""
-
-    def __init__(self, name: str, version: str, **kwargs):
-        assert version == "2023-09-26", "Only v2023-09-26 is supported"
-        super().__init__(
-            name=name, version=Version(version.replace("-", ".")), **kwargs
-        )
-        self.version_str = version
-        self.data_url = (
-            f"https://object.pouta.csc.fi/Tatoeba-Challenge-v{version}/{name}.tar"
-        )
-
-
-class TatoebaChallenge(GeneratorBasedBuilder):
-    """Tatoeba challenge dataset."""
-
-    BUILDER_CONFIG_CLASS = TatoebaChallengeConfig
-    BUILDER_CONFIGS = [
-        TatoebaChallengeConfig(name="chv-eng", version="2023-09-26"),
-        TatoebaChallengeConfig(name="chv-rus", version="2023-09-26"),
-    ]
-
-    def _info(self) -> DatasetInfo:
-        src, trg = self.config.name.split("-")
-        return DatasetInfo(
-            description="""
-               The Tatoeba Translation Challenge.
-               You can find more about the data here: https://github.com/Helsinki-NLP/Tatoeba-Challenge
-
-                Here we have only Chuvash-English subset.
-               We do not use official dataset https://huggingface.co/datasets/Helsinki-NLP/tatoeba_mt
-               here because chv-eng of the dataset contains only test split.
-               """,
-            features=Features(
-                {
-                    "id": Value("string"),
-                    src: Value("string"),
-                    trg: Value("string"),
-                }
-            ),
-            supervised_keys=None,
-            homepage="https://github.com/Helsinki-NLP/Tatoeba-Challenge",
-            citation="""
-           @inproceedings{tiedemann-2020-tatoeba,
-               title = "The {T}atoeba {T}ranslation {C}hallenge {--} {R}ealistic Data Sets for Low Resource and Multilingual {MT}",
-               author = {Tiedemann, J{\"o}rg},
-               booktitle = "Proceedings of the Fifth Conference on Machine Translation",
-               month = nov,
-               year = "2020",
-               address = "Online",
-               publisher = "Association for Computational Linguistics",
-               url = "https://www.aclweb.org/anthology/2020.wmt-1.139",
-               pages = "1174--1182"
-           }
-           """,
-        )
-
-    def _split_generators(
-        self, dl_manager: Union[DownloadManager, StreamingDownloadManager]
-    ):
-        dl_dir = dl_manager.download_and_extract(self.config.data_url)
-        assert isinstance(dl_dir, str)
-
-        path_to_folder = (
-            Path(dl_dir)
-            / "data"
-            / "release"
-            / f"v{self.config.version_str}"
-            / self.config.name
-        )
-        return [
-            SplitGenerator(
-                name=Split.TRAIN._name,
-                gen_kwargs={
-                    "langs": path_to_folder / "train.id.gz",
-                    "src": path_to_folder / "train.src.gz",
-                    "trg": path_to_folder / "train.trg.gz",
-                },
-            ),
-            SplitGenerator(
-                name=Split.TEST._name,
-                gen_kwargs={
-                    "langs": path_to_folder / "test.id",
-                    "src": path_to_folder / "test.src",
-                    "trg": path_to_folder / "test.trg",
-                },
-            ),
-        ]
-
-    def _generate_examples(self, langs: Path, src: Path, trg: Path):
-        if langs.suffix == ".gz":
-            assert src.suffix == trg.suffix
-            assert trg.suffix == langs.suffix
-
-            opener = gzip.open
-        else:
-            opener = open
-
-        with opener(langs, "rb") as langs_src:
-            with opener(src, "rb") as src_src:
-                with opener(trg, "rb") as trg_src:
-                    for id_, (langs_line, src_line, trg_line) in enumerate(
-                        zip(langs_src, src_src, trg_src)
-                    ):
-                        langs_row = langs_line.decode("utf8").strip().split("\t")
-                        # train contains 3 symbols
-                        if len(langs_row) == 3:
-                            _, src_lang, trg_lang = langs_row
-                        else:
-                            src_lang, trg_lang = langs_row
-
-                        yield (
-                            id_,
-                            {
-                                "id": id_,
-                                src_lang: src_line.decode("utf8").strip(),
-                                trg_lang: trg_line.decode("utf8").strip(),
-                            },
-                        )