Convert dataset to Parquet (#2)

- Convert dataset to Parquet (172cd31f93dacfda9bf86f4c626b6d01f99653b2)
- Delete loading script (88eed5db6680341672d438ab278cf605abdc54e6)

README.md

@@ -17,9 +17,9 @@ source_datasets:
 task_categories:
 - translation
 task_ids: []
-paperswithcode_id: null
 pretty_name: OpusTedtalks
 dataset_info:
+  config_name: en-hr
   features:
   - name: id
     dtype: string
@@ -29,13 +29,17 @@ dataset_info:
         languages:
         - en
         - hr
-  config_name: en-hr
   splits:
   - name: train
-    num_bytes: 15249417
+    num_bytes: 15249309
     num_examples: 86348
-  download_size: 5639306
-  dataset_size: 15249417
+  download_size: 9932158
+  dataset_size: 15249309
+configs:
+- config_name: en-hr
+  data_files:
+  - split: train
+    path: en-hr/train-*
 ---
 
 # Dataset Card for OpusTedtalks

en-hr/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:17eaa0f05b079e94d2ea39186f44369a879bd2fec48dbd8d1dbb902bb2455cce
+size 9932158

opus_tedtalks.py

@@ -1,121 +0,0 @@
-# coding=utf-8
-# Copyright 2020 HuggingFace Datasets Authors.
-#
-# 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.
-
-# Lint as: python3
-import os
-
-import datasets
-
-
-_DESCRIPTION = """\
-This is a Croatian-English parallel corpus of transcribed and translated TED talks, originally extracted from https://wit3.fbk.eu. The corpus is compiled by Željko Agić and is taken from http://lt.ffzg.hr/zagic provided under the CC-BY-NC-SA license.
-2 languages, total number of files: 2
-total number of tokens: 2.81M
-total number of sentence fragments: 0.17M
-"""
-_HOMEPAGE_URL = "http://opus.nlpl.eu/TedTalks.php"
-_CITATION = """\
-@InProceedings{TIEDEMANN12.463,
-  author = {J{\"o}rg Tiedemann},
-  title = {Parallel Data, Tools and Interfaces in OPUS},
-  booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
-  year = {2012},
-  month = {may},
-  date = {23-25},
-  address = {Istanbul, Turkey},
-  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Ugur Dogan and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis},
-  publisher = {European Language Resources Association (ELRA)},
-  isbn = {978-2-9517408-7-7},
-  language = {english}
- }
-"""
-
-_VERSION = "1.0.0"
-_BASE_NAME = "TedTalks.{}.{}"
-_BASE_URL = "https://object.pouta.csc.fi/OPUS-TedTalks/v1/moses/{}-{}.txt.zip"
-_LANGUAGE_PAIRS = [
-    ("en", "hr"),
-]
-
-
-class TedTalksConfig(datasets.BuilderConfig):
-    def __init__(self, *args, lang1=None, lang2=None, **kwargs):
-        super().__init__(
-            *args,
-            name=f"{lang1}-{lang2}",
-            **kwargs,
-        )
-        self.lang1 = lang1
-        self.lang2 = lang2
-
-
-class OpusTedtalks(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIGS = [
-        TedTalksConfig(
-            lang1=lang1,
-            lang2=lang2,
-            description=f"Translating {lang1} to {lang2} or vice versa",
-            version=datasets.Version(_VERSION),
-        )
-        for lang1, lang2 in _LANGUAGE_PAIRS
-    ]
-    BUILDER_CONFIG_CLASS = TedTalksConfig
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "translation": datasets.Translation(languages=(self.config.lang1, self.config.lang2)),
-                },
-            ),
-            supervised_keys=None,
-            homepage=_HOMEPAGE_URL,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        def _base_url(lang1, lang2):
-            return _BASE_URL.format(lang1, lang2)
-
-        download_url = _base_url(self.config.lang1, self.config.lang2)
-        path = dl_manager.download_and_extract(download_url)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"datapath": path},
-            )
-        ]
-
-    def _generate_examples(self, datapath):
-        l1, l2 = self.config.lang1, self.config.lang2
-        folder = l1 + "-" + l2
-        l1_file = _BASE_NAME.format(folder, l1)
-        l2_file = _BASE_NAME.format(folder, l2)
-        l1_path = os.path.join(datapath, l1_file)
-        l2_path = os.path.join(datapath, l2_file)
-        with open(l1_path, encoding="utf-8") as f1, open(l2_path, encoding="utf-8") as f2:
-            for sentence_counter, (x, y) in enumerate(zip(f1, f2)):
-                x = x.strip()
-                y = y.strip()
-                result = (
-                    sentence_counter,
-                    {
-                        "id": str(sentence_counter),
-                        "translation": {l1: x, l2: y},
-                    },
-                )
-                yield result