Datasets:
File size: 6,772 Bytes
6300a14 02a6810 e5c6370 6300a14 f96c321 6300a14 957151e 6300a14 5e8f719 6300a14 f96c321 6300a14 f96c321 6300a14 c9a9415 6300a14 c9a9415 6300a14 c9a9415 6300a14 c9a9415 6300a14 c9a9415 6300a14 c9a9415 6300a14 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 |
# 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
_HOMEPAGE = "https://sites.google.com/site/iwsltevaluation2017/TED-tasks"
_DESCRIPTION = """\
The IWSLT 2017 Multilingual Task addresses text translation, including zero-shot translation, with a single MT system across all directions including English, German, Dutch, Italian and Romanian. As unofficial task, conventional bilingual text translation is offered between English and Arabic, French, Japanese, Chinese, German and Korean.
"""
_CITATION = """\
@inproceedings{cettolo-etal-2017-overview,
title = "Overview of the {IWSLT} 2017 Evaluation Campaign",
author = {Cettolo, Mauro and
Federico, Marcello and
Bentivogli, Luisa and
Niehues, Jan and
St{\\"u}ker, Sebastian and
Sudoh, Katsuhito and
Yoshino, Koichiro and
Federmann, Christian},
booktitle = "Proceedings of the 14th International Conference on Spoken Language Translation",
month = dec # " 14-15",
year = "2017",
address = "Tokyo, Japan",
publisher = "International Workshop on Spoken Language Translation",
url = "https://aclanthology.org/2017.iwslt-1.1",
pages = "2--14",
}
"""
REPO_URL = "https://huggingface.co/datasets/bbaaaa/iwslt14-de-en/resolve/main/"
URL = REPO_URL + "data/de-en.zip"
class IWSLT2017Config(datasets.BuilderConfig):
"""BuilderConfig for NewDataset"""
def __init__(self, pair, **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
super().__init__(**kwargs)
class IWSLT2017(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="de-en",
description="A small dataset",
version=datasets.Version("1.0.0"),
pair='de-en',
)
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{"translation": datasets.features.Translation(languages=self.config.pair.split("-"))}
),
homepage=_HOMEPAGE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
source, target = self.config.pair.split("-")
bi_url = URL
dl_dir = dl_manager.download_and_extract(bi_url)
data_dir = os.path.join(dl_dir, f"{source}-{target}")
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"source_files": [
os.path.join(
data_dir,
f"train.{source}",
)
],
"target_files": [
os.path.join(
data_dir,
f"train.{target}",
)
],
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"source_files": [
os.path.join(
data_dir,
f"test.{source}",
)
],
"target_files": [
os.path.join(
data_dir,
f"test.{target}",
)
],
},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"source_files": [
os.path.join(
data_dir,
f"valid.{source}",
)
],
"target_files": [
os.path.join(
data_dir,
f"valid.{target}",
)
],
},
),
]
def _generate_examples(self, source_files, target_files):
"""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
|