Convert dataset to Parquet (#3)

- Convert dataset to Parquet (da9abc5fe22156e058e5469f43de34c7b7fa53aa)
- Add 'en2es' config data files (acac9f3acb590238d6fa57b70404804ef52aa453)
- Add 'en2fr' config data files (fe26a6020e2be24899e912c6605888ceae760769)
- Delete loading script (692be6f59a3c88e907fda82e987fdebd99f267b8)

README.md

@@ -59,10 +59,10 @@ dataset_info:
           '1': sentence_data
   splits:
   - name: train
-    num_bytes: 664252
+    num_bytes: 664244
     num_examples: 4061
-  download_size: 3521416
-  dataset_size: 664252
+  download_size: 332039
+  dataset_size: 664244
 - config_name: en2cs
   features:
   - name: translation
@@ -159,10 +159,10 @@ dataset_info:
           '1': sentence_data
   splits:
   - name: train
-    num_bytes: 555218
+    num_bytes: 555210
     num_examples: 4303
-  download_size: 3521416
-  dataset_size: 555218
+  download_size: 308680
+  dataset_size: 555210
 - config_name: en2et
   features:
   - name: translation
@@ -219,10 +219,10 @@ dataset_info:
           '1': sentence_data
   splits:
   - name: train
-    num_bytes: 575579
+    num_bytes: 575571
     num_examples: 4476
-  download_size: 3521416
-  dataset_size: 575579
+  download_size: 321064
+  dataset_size: 575571
 - config_name: en2hu
   features:
   - name: translation
@@ -523,6 +523,19 @@ dataset_info:
     num_examples: 3198
   download_size: 3521416
   dataset_size: 328267
+configs:
+- config_name: en2bg
+  data_files:
+  - split: train
+    path: en2bg/train-*
+- config_name: en2es
+  data_files:
+  - split: train
+    path: en2es/train-*
+- config_name: en2fr
+  data_files:
+  - split: train
+    path: en2fr/train-*
 ---
 
 # Dataset Card for Europa Education and Culture Translation Memory (EAC-TM)

en2bg/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9de4205b34d914bbffa91fd28db9a51adaf762f56c1a970b29fd58f8d6c94b3a
+size 332039

en2es/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3b90ac0cc93ec7b3a385661b5c075a837dd5ec64236bf40430e29a1dbf913b1c
+size 308680

en2fr/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3a6e6c1d3c67a0f3d6afe881d83b2827efdefd2d64fb33a06ac4b3e3aa6b747a
+size 321064

europa_eac_tm.py

@@ -1,226 +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.
-"""European commission Joint Reasearch Center's Education And Culture Translation Memory dataset"""
-
-
-import os
-from itertools import repeat
-from xml.etree import ElementTree
-
-import datasets
-
-
-_CITATION = """\
-@Article{Steinberger2014,
-        author={Steinberger, Ralf
-                and Ebrahim, Mohamed
-                and Poulis, Alexandros
-                and Carrasco-Benitez, Manuel
-                and Schl{\"u}ter, Patrick
-                and Przybyszewski, Marek
-                and Gilbro, Signe},
-        title={An overview of the European Union's highly multilingual parallel corpora},
-        journal={Language Resources and Evaluation},
-        year={2014},
-        month={Dec},
-        day={01},
-        volume={48},
-        number={4},
-        pages={679-707},
-        issn={1574-0218},
-        doi={10.1007/s10579-014-9277-0},
-        url={https://doi.org/10.1007/s10579-014-9277-0}
-}
-"""
-
-_DESCRIPTION = """\
-In October 2012, the European Union's (EU) Directorate General for Education and Culture ( DG EAC) released a \
-translation memory (TM), i.e. a collection of sentences and their professionally produced translations, in \
-twenty-six languages. This resource bears the name EAC Translation Memory, short EAC-TM.
-
-EAC-TM covers up to 26 languages: 22 official languages of the EU (all except Irish) plus Icelandic, Croatian, \
-Norwegian and Turkish. EAC-TM thus contains translations from English into the following 25 languages: Bulgarian, \
-Czech, Danish, Dutch, Estonian, German, Greek, Finnish, French, Croatian, Hungarian, Icelandic, Italian, Latvian, \
-Lithuanian, Maltese, Norwegian, Polish, Portuguese, Romanian, Slovak, Slovenian, Spanish, Swedish and Turkish.
-
-All documents and sentences were originally written in English (source language is English) and then translated into \
-the other languages. The texts were translated by staff of the National Agencies of the Lifelong Learning and Youth in \
-Action programmes. They are typically professionals in the field of education/youth and EU programmes. They are thus not \
-professional translators, but they are normally native speakers of the target language.
-"""
-
-_HOMEPAGE = "https://ec.europa.eu/jrc/en/language-technologies/eac-translation-memory"
-
-_LICENSE = "\
-Creative Commons Attribution 4.0 International(CC BY 4.0) licence \
-© European Union, 1995-2020"
-
-_VERSION = "1.0.0"
-
-_DATA_URL = "https://wt-public.emm4u.eu/Resources/EAC-TM/EAC-TM-all.zip"
-
-_AVAILABLE_LANGUAGES = (
-    "bg",
-    "cs",
-    "da",
-    "de",
-    "el",
-    "en",
-    "es",
-    "et",
-    "fi",
-    "fr",
-    "hu",
-    "is",
-    "it",
-    "lt",
-    "lv",
-    "mt",
-    "nb",
-    "nl",
-    "pl",
-    "pt",
-    "ro",
-    "sk",
-    "sl",
-    "sv",
-    "tr",
-)
-
-
-def _find_sentence(translation, language):
-    """Util that returns the sentence in the given language from translation, or None if it is not found
-
-    Args:
-        translation: `xml.etree.ElementTree.Element`, xml tree element extracted from the translation memory files.
-        language: `str`, language of interest e.g. 'en'
-
-    Returns: `str` or `None`, can be `None` if the language of interest is not found in the translation
-    """
-    # Retrieve the first <tuv> children of translation having xml:lang tag equal to language
-    namespaces = {"xml": "http://www.w3.org/XML/1998/namespace"}
-    seg_tag = translation.find(path=f".//tuv[@xml:lang='{language}']/seg", namespaces=namespaces)
-    if seg_tag is not None:
-        return seg_tag.text
-    return None
-
-
-class EuropaEacTMConfig(datasets.BuilderConfig):
-    """BuilderConfig for EuropaEacTM"""
-
-    def __init__(self, *args, language_pair=(None, None), **kwargs):
-        """BuilderConfig for EuropaEacTM
-
-        Args:
-            language_pair: pair of languages that will be used for translation. Should
-                contain 2-letter coded strings. First will be used at source and second
-                as target in supervised mode. For example: ("ro", "en").
-            **kwargs: keyword arguments forwarded to super.
-        """
-        name = f"{language_pair[0]}2{language_pair[1]}"
-        description = f"Translation dataset from {language_pair[0]} to {language_pair[1]}"
-        super(EuropaEacTMConfig, self).__init__(
-            *args,
-            name=name,
-            description=description,
-            **kwargs,
-        )
-        source, target = language_pair
-        assert source != target, "Source and target languages must be different}"
-        assert (source in _AVAILABLE_LANGUAGES) and (
-            target in _AVAILABLE_LANGUAGES
-        ), f"Either source language {source} or target language {target} is not supported. Both must be one of : {_AVAILABLE_LANGUAGES}"
-
-        self.language_pair = language_pair
-
-
-# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
-class EuropaEacTM(datasets.GeneratorBasedBuilder):
-    """European Commission Joint Research Center's EAC Translation Memory"""
-
-    FORM_SENTENCE_TYPE = "form_data"
-    REFERENCE_SENTENCE_TYPE = "sentence_data"
-
-    # Only a few language pairs are listed here. You can use config to generate all language pairs !
-    BUILDER_CONFIGS = [
-        EuropaEacTMConfig(language_pair=("en", target), version=_VERSION) for target in ["bg", "es", "fr"]
-    ]
-    BUILDER_CONFIG_CLASS = EuropaEacTMConfig
-
-    def _info(self):
-        source, target = self.config.language_pair
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "translation": datasets.features.Translation(languages=self.config.language_pair),
-                    "sentence_type": datasets.features.ClassLabel(
-                        names=[self.FORM_SENTENCE_TYPE, self.REFERENCE_SENTENCE_TYPE]
-                    ),
-                }
-            ),
-            supervised_keys=(source, target),
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        dl_dir = dl_manager.download_and_extract(_DATA_URL)
-        form_data_file = os.path.join(dl_dir, "EAC_FORMS.tmx")
-        reference_data_file = os.path.join(dl_dir, "EAC_REFRENCE_DATA.tmx")
-        source, target = self.config.language_pair
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "form_data_file": form_data_file,
-                    "reference_data_file": reference_data_file,
-                    "source_language": source,
-                    "target_language": target,
-                },
-            ),
-        ]
-
-    def _generate_examples(
-        self,
-        form_data_file,
-        reference_data_file,
-        source_language,
-        target_language,
-    ):
-        _id = 0
-        for (sentence_type, filepath) in [
-            (self.FORM_SENTENCE_TYPE, form_data_file),
-            (self.REFERENCE_SENTENCE_TYPE, reference_data_file),
-        ]:
-            # Retrieve <tu></tu> tags in the tmx file
-            xml_element_tree = ElementTree.parse(filepath)
-            xml_body_tag = xml_element_tree.getroot().find("body")
-            assert xml_body_tag is not None, f"Invalid data: <body></body> tag not found in {filepath}"
-            translation_units = xml_body_tag.iter("tu")
-
-            # Pair sentence_type and translation_units
-            for sentence_type, translation in zip(repeat(sentence_type), translation_units):
-                source_sentence = _find_sentence(translation=translation, language=source_language)
-                target_sentence = _find_sentence(translation=translation, language=target_language)
-                if source_sentence is None or target_sentence is None:
-                    continue
-                _id += 1
-                sentence_label = 0 if sentence_type == self.FORM_SENTENCE_TYPE else 1
-                yield _id, {
-                    "translation": {source_language: source_sentence, target_language: target_sentence},
-                    "sentence_type": sentence_label,
-                }