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# 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://wit3.fbk.eu/archive/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://wit3.fbk.eu/archive/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("<seg"):
# Remove <seg id="1">.....</seg>
# 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
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