Delete loading script

opus100.py

@@ -1,271 +0,0 @@
-# coding=utf-8
-# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-"""OPUS-100"""
-
-
-import datasets
-
-
-_CITATION = """\
-@misc{zhang2020improving,
-      title={Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation},
-      author={Biao Zhang and Philip Williams and Ivan Titov and Rico Sennrich},
-      year={2020},
-      eprint={2004.11867},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL}
-}
-"""
-
-_DESCRIPTION = """\
-OPUS-100 is English-centric, meaning that all training pairs include English on either the source or target side.
-The corpus covers 100 languages (including English).OPUS-100 contains approximately 55M sentence pairs.
-Of the 99 language pairs, 44 have 1M sentence pairs of training data, 73 have at least 100k, and 95 have at least 10k.
-"""
-
-_URL = {
-    "supervised": "https://object.pouta.csc.fi/OPUS-100/v1.0/opus-100-corpus-{}-v1.0.tar.gz",
-    "zero-shot": "https://object.pouta.csc.fi/OPUS-100/v1.0/opus-100-corpus-zeroshot-v1.0.tar.gz",
-}
-
-_SupervisedLanguagePairs = [
-    "af-en",
-    "am-en",
-    "an-en",
-    "ar-en",
-    "as-en",
-    "az-en",
-    "be-en",
-    "bg-en",
-    "bn-en",
-    "br-en",
-    "bs-en",
-    "ca-en",
-    "cs-en",
-    "cy-en",
-    "da-en",
-    "de-en",
-    "dz-en",
-    "el-en",
-    "en-eo",
-    "en-es",
-    "en-et",
-    "en-eu",
-    "en-fa",
-    "en-fi",
-    "en-fr",
-    "en-fy",
-    "en-ga",
-    "en-gd",
-    "en-gl",
-    "en-gu",
-    "en-ha",
-    "en-he",
-    "en-hi",
-    "en-hr",
-    "en-hu",
-    "en-hy",
-    "en-id",
-    "en-ig",
-    "en-is",
-    "en-it",
-    "en-ja",
-    "en-ka",
-    "en-kk",
-    "en-km",
-    "en-ko",
-    "en-kn",
-    "en-ku",
-    "en-ky",
-    "en-li",
-    "en-lt",
-    "en-lv",
-    "en-mg",
-    "en-mk",
-    "en-ml",
-    "en-mn",
-    "en-mr",
-    "en-ms",
-    "en-mt",
-    "en-my",
-    "en-nb",
-    "en-ne",
-    "en-nl",
-    "en-nn",
-    "en-no",
-    "en-oc",
-    "en-or",
-    "en-pa",
-    "en-pl",
-    "en-ps",
-    "en-pt",
-    "en-ro",
-    "en-ru",
-    "en-rw",
-    "en-se",
-    "en-sh",
-    "en-si",
-    "en-sk",
-    "en-sl",
-    "en-sq",
-    "en-sr",
-    "en-sv",
-    "en-ta",
-    "en-te",
-    "en-tg",
-    "en-th",
-    "en-tk",
-    "en-tr",
-    "en-tt",
-    "en-ug",
-    "en-uk",
-    "en-ur",
-    "en-uz",
-    "en-vi",
-    "en-wa",
-    "en-xh",
-    "en-yi",
-    "en-yo",
-    "en-zh",
-    "en-zu",
-]
-
-_0shotLanguagePairs = [
-    "ar-de",
-    "ar-fr",
-    "ar-nl",
-    "ar-ru",
-    "ar-zh",
-    "de-fr",
-    "de-nl",
-    "de-ru",
-    "de-zh",
-    "fr-nl",
-    "fr-ru",
-    "fr-zh",
-    "nl-ru",
-    "nl-zh",
-    "ru-zh",
-]
-
-
-class Opus100Config(datasets.BuilderConfig):
-    """BuilderConfig for Opus100"""
-
-    def __init__(self, language_pair, **kwargs):
-        super().__init__(**kwargs)
-        """
-
-        Args:
-            language_pair: language pair, you want to load
-            **kwargs: keyword arguments forwarded to super.
-        """
-        self.language_pair = language_pair
-
-
-class Opus100(datasets.GeneratorBasedBuilder):
-    """OPUS-100 is English-centric, meaning that all training pairs include English on either the source or target side."""
-
-    VERSION = datasets.Version("1.0.0")
-
-    BUILDER_CONFIG_CLASS = Opus100Config
-    BUILDER_CONFIGS = [
-        Opus100Config(name=pair, description=_DESCRIPTION, language_pair=pair)
-        for pair in _SupervisedLanguagePairs + _0shotLanguagePairs
-    ]
-
-    def _info(self):
-        src_tag, tgt_tag = self.config.language_pair.split("-")
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features({"translation": datasets.features.Translation(languages=(src_tag, tgt_tag))}),
-            supervised_keys=(src_tag, tgt_tag),
-            homepage="http://opus.nlpl.eu/opus-100.php",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-
-        lang_pair = self.config.language_pair
-        src_tag, tgt_tag = lang_pair.split("-")
-
-        domain = "supervised"
-        if lang_pair in _0shotLanguagePairs:
-            domain = "zero-shot"
-
-        if domain == "supervised":
-            archive = dl_manager.download(_URL["supervised"].format(lang_pair))
-        elif domain == "zero-shot":
-            archive = dl_manager.download(_URL["zero-shot"])
-
-        data_dir = "/".join(["opus-100-corpus", "v1.0", domain, lang_pair])
-        output = []
-
-        test = datasets.SplitGenerator(
-            name=datasets.Split.TEST,
-            # These kwargs will be passed to _generate_examples
-            gen_kwargs={
-                "filepath": f"{data_dir}/opus.{lang_pair}-test.{src_tag}",
-                "labelpath": f"{data_dir}/opus.{lang_pair}-test.{tgt_tag}",
-                "files": dl_manager.iter_archive(archive),
-            },
-        )
-
-        available_files = [path for path, _ in dl_manager.iter_archive(archive)]
-        if f"{data_dir}/opus.{lang_pair}-test.{src_tag}" in available_files:
-            output.append(test)
-
-        if domain == "supervised":
-
-            train = datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "filepath": f"{data_dir}/opus.{lang_pair}-train.{src_tag}",
-                    "labelpath": f"{data_dir}/opus.{lang_pair}-train.{tgt_tag}",
-                    "files": dl_manager.iter_archive(archive),
-                },
-            )
-
-            if f"{data_dir}/opus.{lang_pair}-train.{src_tag}" in available_files:
-                output.append(train)
-
-            valid = datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": f"{data_dir}/opus.{lang_pair}-dev.{src_tag}",
-                    "labelpath": f"{data_dir}/opus.{lang_pair}-dev.{tgt_tag}",
-                    "files": dl_manager.iter_archive(archive),
-                },
-            )
-
-            if f"{data_dir}/opus.{lang_pair}-dev.{src_tag}" in available_files:
-                output.append(valid)
-
-        return output
-
-    def _generate_examples(self, filepath, labelpath, files):
-        """Yields examples."""
-        src_tag, tgt_tag = self.config.language_pair.split("-")
-        src, tgt = None, None
-        for path, f in files:
-            if path == filepath:
-                src = f.read().decode("utf-8").split("\n")[:-1]
-            elif path == labelpath:
-                tgt = f.read().decode("utf-8").split("\n")[:-1]
-            if src is not None and tgt is not None:
-                for idx, (s, t) in enumerate(zip(src, tgt)):
-                    yield idx, {"translation": {src_tag: s, tgt_tag: t}}
-                break