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Create kftt.py

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+ # coding=utf-8
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+ # KFTT Dataset
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+
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+ # Lint as: python3
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+ """The Kyoto Free Translation Task (KFTT) Dataset for Japanese-English machine translation."""
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+
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+
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+ import collections
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+
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+ import datasets
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+
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+
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+ _DESCRIPTION = """\
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+ The Kyoto Free Translation Task is a task for Japanese-English translation that focuses
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+ on Wikipedia articles related to Kyoto. The data used was originally prepared by the
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+ National Institute for Information and Communication Technology (NICT) and released as
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+ the Japanese-English Bilingual Corpus of Wikipedia's Kyoto Articles (we are simply using
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+ the data, NICT does not specifically endorse or sponsor this task).
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+ """
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+
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+ _CITATION = """\
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+ @misc{neubig11kftt,
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+ author = {Graham Neubig},
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+ title = {The {Kyoto} Free Translation Task},
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+ howpublished = {http://www.phontron.com/kftt},
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+ year = {2011}
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+ }
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+ """
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+
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+ _HOMEPAGE = "http://www.phontron.com/kftt/"
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+
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+ _LICENSE = "Creative Commons Attribution-Share-Alike License 3.0 (CC BY-SA 3.0)"
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+
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+ _DATA_URL = "http://www.phontron.com/kftt/download/kftt-data-1.0.tar.gz"
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+
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+ # Tuple that describes a single pair of files with matching translations.
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+ # language_to_file is the map from language (2 letter string: example 'en')
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+ # to the file path in the extracted directory.
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+ TranslateData = collections.namedtuple("TranslateData", ["url", "language_to_file"])
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+
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+
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+ class KFTTConfig(datasets.BuilderConfig):
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+ """BuilderConfig for KFTT."""
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+
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+ def __init__(self, language_pair=(None, None), **kwargs):
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+ """BuilderConfig for KFTT.
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+
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+ Args:
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+ for the `datasets.features.text.TextEncoder` used for the features feature.
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+ language_pair: pair of languages that will be used for translation. Should
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+ contain 2-letter coded strings. First will be used at source and second
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+ as target in supervised mode. For example: ("ja", "en").
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+ **kwargs: keyword arguments forwarded to super.
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+ """
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+ super(KFTTConfig, self).__init__(
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+ name="%s-%s" % (language_pair[0], language_pair[1]),
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+ description="English-Japanese translation dataset.",
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+ version=datasets.Version("1.0.0", ""),
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+ **kwargs,
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+ )
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+
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+ # Validate language pair.
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+ assert "en" in language_pair
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+ assert "ja" in language_pair
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+
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+ self.language_pair = language_pair
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+
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+
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+ class KFTT(datasets.GeneratorBasedBuilder):
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+ """KFTT machine translation dataset."""
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+
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+ BUILDER_CONFIGS = [
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+ KFTTConfig(
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+ language_pair=("en", "ja"),
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+ ),
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+ ]
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+
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+ def _info(self):
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+ source, target = self.config.language_pair
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+ return datasets.DatasetInfo(
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+ description=_DESCRIPTION,
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+ features=datasets.Features(
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+ {"translation": datasets.features.Translation(languages=self.config.language_pair)}
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+ ),
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+ supervised_keys=(source, target),
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+ homepage=_HOMEPAGE,
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+ citation=_CITATION,
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+ license=_LICENSE,
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+ )
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+
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+ def _split_generators(self, dl_manager):
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+ archive = dl_manager.download(_DATA_URL)
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+
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+ source, target = self.config.language_pair
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+ path_tmpl = "kftt-data-1.0/data/orig/kyoto-{split}.{lang}"
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+
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+ files = {}
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+ for split in ("train", "dev", "test", "tune"):
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+ files[split] = {
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+ "source_file": path_tmpl.format(split=split, lang=source),
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+ "target_file": path_tmpl.format(split=split, lang=target),
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+ "files": dl_manager.iter_archive(archive),
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+ }
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+
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+ return [
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+ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs=files["train"]),
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+ datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs=files["dev"]),
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+ datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs=files["test"]),
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+ datasets.SplitGenerator(name=datasets.Split("tune"), gen_kwargs=files["tune"]),
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+ ]
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+
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+ def _generate_examples(self, files, source_file, target_file):
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+ """This function returns the examples in the raw (text) form."""
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+ source_sentences, target_sentences = None, None
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+ for path, f in files:
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+ if path == source_file:
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+ source_sentences = f.read().decode("utf-8").split("\n")
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+ elif path == target_file:
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+ target_sentences = f.read().decode("utf-8").split("\n")
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+ if source_sentences is not None and target_sentences is not None:
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+ break
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+
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+ assert len(target_sentences) == len(source_sentences), "Sizes do not match: %d vs %d for %s vs %s." % (
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+ len(source_sentences),
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+ len(target_sentences),
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+ source_file,
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+ target_file,
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+ )
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+
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+ source, target = self.config.language_pair
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+ for idx, (l1, l2) in enumerate(zip(source_sentences, target_sentences)):
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+ result = {"translation": {source: l1, target: l2}}
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+ # Make sure that both translations are non-empty.
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+ if all(result.values()):
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+ yield idx, result