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"""OPUS-100""" |
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import datasets |
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_CITATION = """\ |
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@misc{zhang2020improving, |
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title={Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation}, |
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author={Biao Zhang and Philip Williams and Ivan Titov and Rico Sennrich}, |
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year={2020}, |
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eprint={2004.11867}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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""" |
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_DESCRIPTION = """\ |
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OPUS-100 is English-centric, meaning that all training pairs include English on either the source or target side. |
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The corpus covers 100 languages (including English).OPUS-100 contains approximately 55M sentence pairs. |
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Of the 99 language pairs, 44 have 1M sentence pairs of training data, 73 have at least 100k, and 95 have at least 10k. |
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""" |
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_URL = { |
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"supervised": "https://object.pouta.csc.fi/OPUS-100/v1.0/opus-100-corpus-{}-v1.0.tar.gz", |
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"zero-shot": "https://object.pouta.csc.fi/OPUS-100/v1.0/opus-100-corpus-zeroshot-v1.0.tar.gz", |
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} |
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_SupervisedLanguagePairs = [ |
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"af-en", |
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"am-en", |
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"an-en", |
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"ar-en", |
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"as-en", |
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"az-en", |
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"be-en", |
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"bg-en", |
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"bn-en", |
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"br-en", |
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"bs-en", |
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"ca-en", |
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"cs-en", |
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"cy-en", |
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"da-en", |
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"de-en", |
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"dz-en", |
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"el-en", |
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"en-eo", |
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"en-es", |
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"en-et", |
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"en-eu", |
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"en-fa", |
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"en-fi", |
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"en-fr", |
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"en-fy", |
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"en-ga", |
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"en-gd", |
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"en-gl", |
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"en-gu", |
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"en-ha", |
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"en-he", |
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"en-hi", |
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"en-hr", |
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"en-hu", |
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"en-hy", |
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"en-id", |
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"en-ig", |
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"en-is", |
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"en-it", |
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"en-ja", |
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"en-ka", |
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"en-kk", |
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"en-km", |
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"en-ko", |
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"en-kn", |
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"en-ku", |
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"en-ky", |
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"en-li", |
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"en-lt", |
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"en-lv", |
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"en-mg", |
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"en-mk", |
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"en-ml", |
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"en-mn", |
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"en-mr", |
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"en-ms", |
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"en-mt", |
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"en-my", |
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"en-nb", |
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"en-ne", |
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"en-nl", |
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"en-nn", |
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"en-no", |
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"en-oc", |
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"en-or", |
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"en-pa", |
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"en-pl", |
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"en-ps", |
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"en-pt", |
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"en-ro", |
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"en-ru", |
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"en-rw", |
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"en-se", |
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"en-sh", |
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"en-si", |
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"en-sk", |
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"en-sl", |
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"en-sq", |
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"en-sr", |
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"en-sv", |
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"en-ta", |
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"en-te", |
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"en-tg", |
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"en-th", |
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"en-tk", |
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"en-tr", |
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"en-tt", |
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"en-ug", |
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"en-uk", |
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"en-ur", |
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"en-uz", |
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"en-vi", |
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"en-wa", |
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"en-xh", |
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"en-yi", |
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"en-yo", |
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"en-zh", |
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"en-zu", |
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] |
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_0shotLanguagePairs = [ |
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"ar-de", |
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"ar-fr", |
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"ar-nl", |
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"ar-ru", |
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"ar-zh", |
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"de-fr", |
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"de-nl", |
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"de-ru", |
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"de-zh", |
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"fr-nl", |
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"fr-ru", |
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"fr-zh", |
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"nl-ru", |
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"nl-zh", |
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"ru-zh", |
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] |
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class Opus100Config(datasets.BuilderConfig): |
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"""BuilderConfig for Opus100""" |
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def __init__(self, language_pair, **kwargs): |
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super().__init__(**kwargs) |
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""" |
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Args: |
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language_pair: language pair, you want to load |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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self.language_pair = language_pair |
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class Opus100(datasets.GeneratorBasedBuilder): |
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"""OPUS-100 is English-centric, meaning that all training pairs include English on either the source or target side.""" |
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VERSION = datasets.Version("1.0.0") |
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BUILDER_CONFIG_CLASS = Opus100Config |
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BUILDER_CONFIGS = [ |
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Opus100Config(name=pair, description=_DESCRIPTION, language_pair=pair) |
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for pair in _SupervisedLanguagePairs + _0shotLanguagePairs |
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] |
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def _info(self): |
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src_tag, tgt_tag = self.config.language_pair.split("-") |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features({"translation": datasets.features.Translation(languages=(src_tag, tgt_tag))}), |
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supervised_keys=(src_tag, tgt_tag), |
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homepage="http://opus.nlpl.eu/opus-100.php", |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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lang_pair = self.config.language_pair |
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src_tag, tgt_tag = lang_pair.split("-") |
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domain = "supervised" |
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if lang_pair in _0shotLanguagePairs: |
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domain = "zero-shot" |
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if domain == "supervised": |
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archive = dl_manager.download(_URL["supervised"].format(lang_pair)) |
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elif domain == "zero-shot": |
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archive = dl_manager.download(_URL["zero-shot"]) |
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data_dir = "/".join(["opus-100-corpus", "v1.0", domain, lang_pair]) |
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output = [] |
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test = datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={ |
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"filepath": f"{data_dir}/opus.{lang_pair}-test.{src_tag}", |
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"labelpath": f"{data_dir}/opus.{lang_pair}-test.{tgt_tag}", |
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"files": dl_manager.iter_archive(archive), |
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}, |
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) |
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available_files = [path for path, _ in dl_manager.iter_archive(archive)] |
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if f"{data_dir}/opus.{lang_pair}-test.{src_tag}" in available_files: |
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output.append(test) |
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if domain == "supervised": |
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train = datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"filepath": f"{data_dir}/opus.{lang_pair}-train.{src_tag}", |
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"labelpath": f"{data_dir}/opus.{lang_pair}-train.{tgt_tag}", |
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"files": dl_manager.iter_archive(archive), |
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}, |
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) |
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if f"{data_dir}/opus.{lang_pair}-train.{src_tag}" in available_files: |
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output.append(train) |
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valid = datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={ |
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"filepath": f"{data_dir}/opus.{lang_pair}-dev.{src_tag}", |
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"labelpath": f"{data_dir}/opus.{lang_pair}-dev.{tgt_tag}", |
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"files": dl_manager.iter_archive(archive), |
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}, |
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) |
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if f"{data_dir}/opus.{lang_pair}-dev.{src_tag}" in available_files: |
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output.append(valid) |
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return output |
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def _generate_examples(self, filepath, labelpath, files): |
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"""Yields examples.""" |
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src_tag, tgt_tag = self.config.language_pair.split("-") |
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src, tgt = None, None |
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for path, f in files: |
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if path == filepath: |
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src = f.read().decode("utf-8").split("\n")[:-1] |
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elif path == labelpath: |
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tgt = f.read().decode("utf-8").split("\n")[:-1] |
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if src is not None and tgt is not None: |
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for idx, (s, t) in enumerate(zip(src, tgt)): |
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yield idx, {"translation": {src_tag: s, tgt_tag: t}} |
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break |
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