# 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. """IWSLT 2017 dataset """ import os import datasets _CITATION = """\ @inproceedings{cettoloEtAl:EAMT2012, Address = {Trento, Italy}, Author = {Mauro Cettolo and Christian Girardi and Marcello Federico}, Booktitle = {Proceedings of the 16$^{th}$ Conference of the European Association for Machine Translation (EAMT)}, Date = {28-30}, Month = {May}, Pages = {261--268}, Title = {WIT$^3$: Web Inventory of Transcribed and Translated Talks}, Year = {2012}} """ _DESCRIPTION = """\ The IWSLT 2017 Evaluation Campaign includes a multilingual TED Talks MT task. The languages involved are five: German, English, Italian, Dutch, Romanian. For each language pair, training and development sets are available through the entry of the table below: by clicking, an archive will be downloaded which contains the sets and a README file. Numbers in the table refer to millions of units (untokenized words) of the target side of all parallel training sets. """ MULTI_URL = "https://huggingface.co/datasets/iwslt2017/resolve/ebd7c60d9800c2a1be010a227e5f0a2363730f7a/data/2017-01-trnmted/texts/DeEnItNlRo/DeEnItNlRo/DeEnItNlRo-DeEnItNlRo.tgz" class IWSLT2017Config(datasets.BuilderConfig): """BuilderConfig for NewDataset""" def __init__(self, pair, is_multilingual, **kwargs): """ Args: pair: the language pair to consider is_multilingual: Is this pair in the multilingual dataset (download source is different) **kwargs: keyword arguments forwarded to super. """ self.pair = pair self.is_multilingual = is_multilingual super().__init__(**kwargs) # XXX: Artificially removed DE from here, as it also exists within bilingual data MULTI_LANGUAGES = ["en", "it", "nl", "ro"] BI_LANGUAGES = ["ar", "de", "en", "fr", "ja", "ko", "zh"] MULTI_PAIRS = [f"{source}-{target}" for source in MULTI_LANGUAGES for target in MULTI_LANGUAGES if source != target] BI_PAIRS = [ f"{source}-{target}" for source in BI_LANGUAGES for target in BI_LANGUAGES if source != target and (source == "en" or target == "en") ] PAIRS = MULTI_PAIRS + BI_PAIRS class IWSLT217(datasets.GeneratorBasedBuilder): """The IWSLT 2017 Evaluation Campaign includes a multilingual TED Talks MT task.""" VERSION = datasets.Version("1.0.0") # This is an example of a dataset with multiple configurations. # If you don't want/need to define several sub-sets in your dataset, # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes. BUILDER_CONFIG_CLASS = IWSLT2017Config BUILDER_CONFIGS = [ IWSLT2017Config( name="iwslt2017-" + pair, description="A small dataset", version=datasets.Version("1.0.0"), pair=pair, is_multilingual=pair in MULTI_PAIRS, ) for pair in PAIRS ] def _info(self): return datasets.DatasetInfo( # This is the description that will appear on the datasets page. description=_DESCRIPTION, # datasets.features.FeatureConnectors features=datasets.Features( {"translation": datasets.features.Translation(languages=self.config.pair.split("-"))} ), # If there's a common (input, target) tuple from the features, # specify them here. They'll be used if as_supervised=True in # builder.as_dataset. supervised_keys=None, # Homepage of the dataset for documentation homepage="https://sites.google.com/site/iwsltevaluation2017/TED-tasks", citation=_CITATION, ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" source, target = self.config.pair.split("-") if self.config.is_multilingual: dl_dir = dl_manager.download_and_extract(MULTI_URL) data_dir = os.path.join(dl_dir, "DeEnItNlRo-DeEnItNlRo") years = [2010] else: bi_url = f"https://huggingface.co/datasets/iwslt2017/resolve/ebd7c60d9800c2a1be010a227e5f0a2363730f7a/data/2017-01-trnted/texts/{source}/{target}/{source}-{target}.tgz" dl_dir = dl_manager.download_and_extract(bi_url) data_dir = os.path.join(dl_dir, f"{source}-{target}") years = [2010, 2011, 2012, 2013, 2014, 2015] return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, # These kwargs will be passed to _generate_examples gen_kwargs={ "source_files": [ os.path.join( data_dir, f"train.tags.{self.config.pair}.{source}", ) ], "target_files": [ os.path.join( data_dir, f"train.tags.{self.config.pair}.{target}", ) ], "split": "train", }, ), datasets.SplitGenerator( name=datasets.Split.TEST, # These kwargs will be passed to _generate_examples gen_kwargs={ "source_files": [ os.path.join( data_dir, f"IWSLT17.TED.tst{year}.{self.config.pair}.{source}.xml", ) for year in years ], "target_files": [ os.path.join( data_dir, f"IWSLT17.TED.tst{year}.{self.config.pair}.{target}.xml", ) for year in years ], "split": "test", }, ), datasets.SplitGenerator( name=datasets.Split.VALIDATION, # These kwargs will be passed to _generate_examples gen_kwargs={ "source_files": [ os.path.join( data_dir, f"IWSLT17.TED.dev2010.{self.config.pair}.{source}.xml", ) ], "target_files": [ os.path.join( data_dir, f"IWSLT17.TED.dev2010.{self.config.pair}.{target}.xml", ) ], "split": "dev", }, ), ] def _generate_examples(self, source_files, target_files, split): """Yields examples.""" id_ = 0 source, target = self.config.pair.split("-") for source_file, target_file in zip(source_files, target_files): with open(source_file, "r", encoding="utf-8") as sf: with open(target_file, "r", encoding="utf-8") as tf: for source_row, target_row in zip(sf, tf): source_row = source_row.strip() target_row = target_row.strip() if source_row.startswith("<"): if source_row.startswith("..... # Very simple code instead of regex or xml parsing part1 = source_row.split(">")[1] source_row = part1.split("<")[0] part1 = target_row.split(">")[1] target_row = part1.split("<")[0] source_row = source_row.strip() target_row = target_row.strip() else: continue yield id_, {"translation": {source: source_row, target: target_row}} id_ += 1