Upload tatoeba.py with huggingface_hub
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tatoeba.py
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| 1 |
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from pathlib import Path
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| 2 |
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from typing import Dict, List, Tuple
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| 3 |
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| 4 |
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import datasets
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| 5 |
+
from datasets.download.download_manager import DownloadManager
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+
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| 7 |
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from seacrowd.utils import schemas
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| 8 |
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from seacrowd.utils.configs import SEACrowdConfig
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| 9 |
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from seacrowd.utils.constants import Licenses, Tasks
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| 10 |
+
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| 11 |
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_CITATION = """\
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| 12 |
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@article{tatoeba,
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| 13 |
+
title = {Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond},
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| 14 |
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author = {Mikel, Artetxe and Holger, Schwenk,},
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| 15 |
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journal = {arXiv:1812.10464v2},
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| 16 |
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year = {2018}
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| 17 |
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}
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| 18 |
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"""
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| 19 |
+
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| 20 |
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_LOCAL = False
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| 21 |
+
_LANGUAGES = ["ind", "vie", "tgl", "jav", "tha", "eng"]
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| 22 |
+
_DATASETNAME = "tatoeba"
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| 23 |
+
_DESCRIPTION = """\
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| 24 |
+
This dataset is a subset of the Tatoeba corpus containing language pairs for Indonesian, Vietnamese, Tagalog, Javanese, and Thai.
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| 25 |
+
The original dataset description can be found below:
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| 26 |
+
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| 27 |
+
This data is extracted from the Tatoeba corpus, dated Saturday 2018/11/17.
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| 28 |
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For each languages, we have selected 1000 English sentences and their translations, if available. Please check
|
| 29 |
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this paper for a description of the languages, their families and scripts as well as baseline results.
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| 30 |
+
Please note that the English sentences are not identical for all language pairs. This means that the results are
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| 31 |
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not directly comparable across languages. In particular, the sentences tend to have less variety for several
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| 32 |
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low-resource languages, e.g. "Tom needed water", "Tom needs water", "Tom is getting water", ...
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| 33 |
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"""
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| 34 |
+
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| 35 |
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_HOMEPAGE = "https://github.com/facebookresearch/LASER/blob/main/data/tatoeba/v1/README.md"
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| 36 |
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_LICENSE = Licenses.APACHE_2_0.value
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| 37 |
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_URL = "https://github.com/facebookresearch/LASER/raw/main/data/tatoeba/v1/"
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| 38 |
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| 39 |
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_SUPPORTED_TASKS = [Tasks.MACHINE_TRANSLATION]
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| 40 |
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_SOURCE_VERSION = "1.0.0"
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| 41 |
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_SEACROWD_VERSION = "2024.06.20"
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| 42 |
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| 43 |
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| 44 |
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class TatoebaDataset(datasets.GeneratorBasedBuilder):
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| 45 |
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"""Tatoeba subset for Indonesian, Vietnamese, Tagalog, Javanese, and Thai."""
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| 46 |
+
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| 47 |
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SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
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| 48 |
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SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION)
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| 49 |
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| 50 |
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SEACROWD_SCHEMA_NAME = "t2t"
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| 51 |
+
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| 52 |
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# Add configurations for loading a dataset per language.
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| 53 |
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dataset_names = sorted([f"tatoeba_{lang}_eng" for lang in _LANGUAGES[:-1]]) + sorted([f"tatoeba_eng_{lang}" for lang in _LANGUAGES[:-1]])
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| 54 |
+
BUILDER_CONFIGS = []
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| 55 |
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for name in dataset_names:
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| 56 |
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source_config = SEACrowdConfig(
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| 57 |
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name=f"{name}_source",
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| 58 |
+
version=SOURCE_VERSION,
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| 59 |
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description=f"{_DATASETNAME} source schema",
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| 60 |
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schema="source",
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| 61 |
+
subset_id=name,
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| 62 |
+
)
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| 63 |
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BUILDER_CONFIGS.append(source_config)
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| 64 |
+
seacrowd_config = SEACrowdConfig(
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| 65 |
+
name=f"{name}_seacrowd_{SEACROWD_SCHEMA_NAME}",
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| 66 |
+
version=SEACROWD_VERSION,
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| 67 |
+
description=f"{_DATASETNAME} SEACrowd schema",
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| 68 |
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schema=f"seacrowd_{SEACROWD_SCHEMA_NAME}",
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| 69 |
+
subset_id=name,
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| 70 |
+
)
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| 71 |
+
BUILDER_CONFIGS.append(seacrowd_config)
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| 72 |
+
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| 73 |
+
# Add configuration that allows loading all datasets at once.
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| 74 |
+
BUILDER_CONFIGS.extend(
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| 75 |
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[
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| 76 |
+
# tatoeba_source
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| 77 |
+
SEACrowdConfig(
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| 78 |
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name=f"{_DATASETNAME}_source",
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| 79 |
+
version=SOURCE_VERSION,
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| 80 |
+
description=f"{_DATASETNAME} source schema (all)",
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| 81 |
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schema="source",
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| 82 |
+
subset_id=_DATASETNAME,
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| 83 |
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),
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| 84 |
+
# tatoeba_seacrowd_t2t
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| 85 |
+
SEACrowdConfig(
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| 86 |
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name=f"{_DATASETNAME}_seacrowd_{SEACROWD_SCHEMA_NAME}",
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| 87 |
+
version=SEACROWD_VERSION,
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| 88 |
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description=f"{_DATASETNAME} SEACrowd schema (all)",
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| 89 |
+
schema=f"seacrowd_{SEACROWD_SCHEMA_NAME}",
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| 90 |
+
subset_id=_DATASETNAME,
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| 91 |
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),
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| 92 |
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]
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| 93 |
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)
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| 94 |
+
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| 95 |
+
# Choose first language as default
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| 96 |
+
DEFAULT_CONFIG_NAME = f"{_DATASETNAME}_source"
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| 97 |
+
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| 98 |
+
def _info(self) -> datasets.DatasetInfo:
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| 99 |
+
if self.config.schema == "source":
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| 100 |
+
features = datasets.Features(
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| 101 |
+
{
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| 102 |
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"source_sentence": datasets.Value("string"),
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| 103 |
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"target_sentence": datasets.Value("string"),
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| 104 |
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"source_lang": datasets.Value("string"),
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| 105 |
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"target_lang": datasets.Value("string"),
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| 106 |
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}
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| 107 |
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)
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| 108 |
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elif self.config.schema == f"seacrowd_{self.SEACROWD_SCHEMA_NAME}":
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| 109 |
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features = schemas.text2text_features
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| 110 |
+
return datasets.DatasetInfo(
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| 111 |
+
description=_DESCRIPTION,
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| 112 |
+
features=features,
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| 113 |
+
homepage=_HOMEPAGE,
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| 114 |
+
license=_LICENSE,
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| 115 |
+
citation=_CITATION,
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| 116 |
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)
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| 117 |
+
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| 118 |
+
def _split_generators(self, dl_manager: DownloadManager) -> List[datasets.SplitGenerator]:
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| 119 |
+
"""Return SplitGenerators."""
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| 120 |
+
language_pairs = []
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| 121 |
+
tatoeba_source_data = []
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| 122 |
+
tatoeba_eng_data = []
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| 123 |
+
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| 124 |
+
lang_1 = self.config.name.split("_")[1]
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| 125 |
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lang_2 = self.config.name.split("_")[2]
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| 126 |
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if lang_1 == "eng":
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| 127 |
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lang = lang_2
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| 128 |
+
else:
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| 129 |
+
lang = lang_1
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| 130 |
+
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| 131 |
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if lang in _LANGUAGES:
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| 132 |
+
# Load data per language
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| 133 |
+
tatoeba_source_data.append(dl_manager.download_and_extract(_URL + f"tatoeba.{lang}-eng.{lang_1}"))
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| 134 |
+
tatoeba_eng_data.append(dl_manager.download_and_extract(_URL + f"tatoeba.{lang}-eng.{lang_2}"))
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| 135 |
+
language_pairs.append((lang_1, lang_2))
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| 136 |
+
else:
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| 137 |
+
# Load examples from all languages at once
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| 138 |
+
# We just want to run this part when tatoeba_source / tatoeba_seacrowd_t2t was chosen.
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| 139 |
+
for lang in _LANGUAGES[:-1]:
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| 140 |
+
tatoeba_source_data.append(dl_manager.download_and_extract(_URL + f"tatoeba.{lang}-eng.{lang}"))
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| 141 |
+
tatoeba_eng_data.append(dl_manager.download_and_extract(_URL + f"tatoeba.{lang}-eng.eng"))
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| 142 |
+
language_pairs.append((lang, "eng"))
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| 143 |
+
return [
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| 144 |
+
datasets.SplitGenerator(
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| 145 |
+
name=datasets.Split.VALIDATION,
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| 146 |
+
gen_kwargs={
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| 147 |
+
"filepaths": (tatoeba_source_data, tatoeba_eng_data),
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| 148 |
+
"split": "dev",
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| 149 |
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"language_pairs": language_pairs,
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| 150 |
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},
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| 151 |
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)
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| 152 |
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]
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| 153 |
+
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| 154 |
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def _generate_examples(self, filepaths: Tuple[List[Path], List[Path]], split: str, language_pairs: List[str]) -> Tuple[int, Dict]:
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| 155 |
+
"""Yield examples as (key, example) tuples"""
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| 156 |
+
source_files, target_files = filepaths
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| 157 |
+
source_sents = []
|
| 158 |
+
target_sents = []
|
| 159 |
+
source_langs = []
|
| 160 |
+
target_langs = []
|
| 161 |
+
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| 162 |
+
for source_file, target_file, (lang_1, lang_2) in zip(source_files, target_files, language_pairs):
|
| 163 |
+
with open(source_file, encoding="utf-8") as f1:
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| 164 |
+
for row in f1:
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| 165 |
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source_sents.append(row.strip())
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| 166 |
+
source_langs.append(lang_1)
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| 167 |
+
with open(target_file, encoding="utf-8") as f2:
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| 168 |
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for row in f2:
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| 169 |
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target_sents.append(row.strip())
|
| 170 |
+
target_langs.append(lang_2)
|
| 171 |
+
|
| 172 |
+
for idx, (source, target, lang_src, lang_tgt) in enumerate(zip(source_sents, target_sents, source_langs, target_langs)):
|
| 173 |
+
if self.config.schema == "source":
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| 174 |
+
example = {
|
| 175 |
+
"source_sentence": source,
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| 176 |
+
"target_sentence": target,
|
| 177 |
+
# The source_lang in the HuggingFace source seems incorrect
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| 178 |
+
# I am overriding it with the actual language code.
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| 179 |
+
"source_lang": lang_src,
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| 180 |
+
"target_lang": lang_tgt,
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| 181 |
+
}
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| 182 |
+
elif self.config.schema == f"seacrowd_{self.SEACROWD_SCHEMA_NAME}":
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| 183 |
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example = {
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| 184 |
+
"id": str(idx),
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| 185 |
+
"text_1": source,
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| 186 |
+
"text_2": target,
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| 187 |
+
# The source_lang in the HuggingFace source seems incorrect
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| 188 |
+
# I am overriding it with the actual language code.
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| 189 |
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"text_1_name": lang_src,
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| 190 |
+
"text_2_name": lang_tgt,
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| 191 |
+
}
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| 192 |
+
yield idx, example
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