Datasets:
wmt
/

Modalities:
Text
Formats:
parquet
Libraries:
Datasets
Dask
License:
albertvillanova HF staff commited on
Commit
617946b
1 Parent(s): 4d4005c

Delete loading script auxiliary file

Browse files
Files changed (1) hide show
  1. wmt_utils.py +0 -1025
wmt_utils.py DELETED
@@ -1,1025 +0,0 @@
1
- # coding=utf-8
2
- # Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
3
- #
4
- # Licensed under the Apache License, Version 2.0 (the "License");
5
- # you may not use this file except in compliance with the License.
6
- # You may obtain a copy of the License at
7
- #
8
- # http://www.apache.org/licenses/LICENSE-2.0
9
- #
10
- # Unless required by applicable law or agreed to in writing, software
11
- # distributed under the License is distributed on an "AS IS" BASIS,
12
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13
- # See the License for the specific language governing permissions and
14
- # limitations under the License.
15
-
16
- # Lint as: python3
17
- """WMT: Translate dataset."""
18
-
19
-
20
- import codecs
21
- import functools
22
- import glob
23
- import gzip
24
- import itertools
25
- import os
26
- import re
27
- import xml.etree.cElementTree as ElementTree
28
-
29
- import datasets
30
-
31
-
32
- logger = datasets.logging.get_logger(__name__)
33
-
34
-
35
- _DESCRIPTION = """\
36
- Translation dataset based on the data from statmt.org.
37
-
38
- Versions exist for different years using a combination of data
39
- sources. The base `wmt` allows you to create a custom dataset by choosing
40
- your own data/language pair. This can be done as follows:
41
-
42
- ```python
43
- from datasets import inspect_dataset, load_dataset_builder
44
-
45
- inspect_dataset("wmt17", "path/to/scripts")
46
- builder = load_dataset_builder(
47
- "path/to/scripts/wmt_utils.py",
48
- language_pair=("fr", "de"),
49
- subsets={
50
- datasets.Split.TRAIN: ["commoncrawl_frde"],
51
- datasets.Split.VALIDATION: ["euelections_dev2019"],
52
- },
53
- )
54
-
55
- # Standard version
56
- builder.download_and_prepare()
57
- ds = builder.as_dataset()
58
-
59
- # Streamable version
60
- ds = builder.as_streaming_dataset()
61
- ```
62
-
63
- """
64
-
65
-
66
- CWMT_SUBSET_NAMES = ["casia2015", "casict2011", "casict2015", "datum2015", "datum2017", "neu2017"]
67
-
68
-
69
- class SubDataset:
70
- """Class to keep track of information on a sub-dataset of WMT."""
71
-
72
- def __init__(self, name, target, sources, url, path, manual_dl_files=None):
73
- """Sub-dataset of WMT.
74
-
75
- Args:
76
- name: `string`, a unique dataset identifier.
77
- target: `string`, the target language code.
78
- sources: `set<string>`, the set of source language codes.
79
- url: `string` or `(string, string)`, URL(s) or URL template(s) specifying
80
- where to download the raw data from. If two strings are provided, the
81
- first is used for the source language and the second for the target.
82
- Template strings can either contain '{src}' placeholders that will be
83
- filled in with the source language code, '{0}' and '{1}' placeholders
84
- that will be filled in with the source and target language codes in
85
- alphabetical order, or all 3.
86
- path: `string` or `(string, string)`, path(s) or path template(s)
87
- specifing the path to the raw data relative to the root of the
88
- downloaded archive. If two strings are provided, the dataset is assumed
89
- to be made up of parallel text files, the first being the source and the
90
- second the target. If one string is provided, both languages are assumed
91
- to be stored within the same file and the extension is used to determine
92
- how to parse it. Template strings should be formatted the same as in
93
- `url`.
94
- manual_dl_files: `<list>(string)` (optional), the list of files that must
95
- be manually downloaded to the data directory.
96
- """
97
- self._paths = (path,) if isinstance(path, str) else path
98
- self._urls = (url,) if isinstance(url, str) else url
99
- self._manual_dl_files = manual_dl_files if manual_dl_files else []
100
- self.name = name
101
- self.target = target
102
- self.sources = set(sources)
103
-
104
- def _inject_language(self, src, strings):
105
- """Injects languages into (potentially) template strings."""
106
- if src not in self.sources:
107
- raise ValueError(f"Invalid source for '{self.name}': {src}")
108
-
109
- def _format_string(s):
110
- if "{0}" in s and "{1}" and "{src}" in s:
111
- return s.format(*sorted([src, self.target]), src=src)
112
- elif "{0}" in s and "{1}" in s:
113
- return s.format(*sorted([src, self.target]))
114
- elif "{src}" in s:
115
- return s.format(src=src)
116
- else:
117
- return s
118
-
119
- return [_format_string(s) for s in strings]
120
-
121
- def get_url(self, src):
122
- return self._inject_language(src, self._urls)
123
-
124
- def get_manual_dl_files(self, src):
125
- return self._inject_language(src, self._manual_dl_files)
126
-
127
- def get_path(self, src):
128
- return self._inject_language(src, self._paths)
129
-
130
-
131
- # Subsets used in the training sets for various years of WMT.
132
- _TRAIN_SUBSETS = [
133
- # pylint:disable=line-too-long
134
- SubDataset(
135
- name="commoncrawl",
136
- target="en", # fr-de pair in commoncrawl_frde
137
- sources={"cs", "de", "es", "fr", "ru"},
138
- url="https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-commoncrawl.zip",
139
- path=("commoncrawl.{src}-en.{src}", "commoncrawl.{src}-en.en"),
140
- ),
141
- SubDataset(
142
- name="commoncrawl_frde",
143
- target="de",
144
- sources={"fr"},
145
- url=(
146
- "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/fr-de/bitexts/commoncrawl.fr.gz",
147
- "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/fr-de/bitexts/commoncrawl.de.gz",
148
- ),
149
- path=("", ""),
150
- ),
151
- SubDataset(
152
- name="czeng_10",
153
- target="en",
154
- sources={"cs"},
155
- url="http://ufal.mff.cuni.cz/czeng/czeng10",
156
- manual_dl_files=["data-plaintext-format.%d.tar" % i for i in range(10)],
157
- # Each tar contains multiple files, which we process specially in
158
- # _parse_czeng.
159
- path=("data.plaintext-format/??train.gz",) * 10,
160
- ),
161
- SubDataset(
162
- name="czeng_16pre",
163
- target="en",
164
- sources={"cs"},
165
- url="http://ufal.mff.cuni.cz/czeng/czeng16pre",
166
- manual_dl_files=["czeng16pre.deduped-ignoring-sections.txt.gz"],
167
- path="",
168
- ),
169
- SubDataset(
170
- name="czeng_16",
171
- target="en",
172
- sources={"cs"},
173
- url="http://ufal.mff.cuni.cz/czeng",
174
- manual_dl_files=["data-plaintext-format.%d.tar" % i for i in range(10)],
175
- # Each tar contains multiple files, which we process specially in
176
- # _parse_czeng.
177
- path=("data.plaintext-format/??train.gz",) * 10,
178
- ),
179
- SubDataset(
180
- # This dataset differs from the above in the filtering that is applied
181
- # during parsing.
182
- name="czeng_17",
183
- target="en",
184
- sources={"cs"},
185
- url="http://ufal.mff.cuni.cz/czeng",
186
- manual_dl_files=["data-plaintext-format.%d.tar" % i for i in range(10)],
187
- # Each tar contains multiple files, which we process specially in
188
- # _parse_czeng.
189
- path=("data.plaintext-format/??train.gz",) * 10,
190
- ),
191
- SubDataset(
192
- name="dcep_v1",
193
- target="en",
194
- sources={"lv"},
195
- url="https://huggingface.co/datasets/wmt/wmt17/resolve/main-zip/translation-task/dcep.lv-en.v1.zip",
196
- path=("dcep.en-lv/dcep.lv", "dcep.en-lv/dcep.en"),
197
- ),
198
- SubDataset(
199
- name="europarl_v7",
200
- target="en",
201
- sources={"cs", "de", "es", "fr"},
202
- url="https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-europarl-v7.zip",
203
- path=("training/europarl-v7.{src}-en.{src}", "training/europarl-v7.{src}-en.en"),
204
- ),
205
- SubDataset(
206
- name="europarl_v7_frde",
207
- target="de",
208
- sources={"fr"},
209
- url=(
210
- "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/fr-de/bitexts/europarl-v7.fr.gz",
211
- "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/fr-de/bitexts/europarl-v7.de.gz",
212
- ),
213
- path=("", ""),
214
- ),
215
- SubDataset(
216
- name="europarl_v8_18",
217
- target="en",
218
- sources={"et", "fi"},
219
- url="https://huggingface.co/datasets/wmt/wmt18/resolve/main-zip/translation-task/training-parallel-ep-v8.zip",
220
- path=("training/europarl-v8.{src}-en.{src}", "training/europarl-v8.{src}-en.en"),
221
- ),
222
- SubDataset(
223
- name="europarl_v8_16",
224
- target="en",
225
- sources={"fi", "ro"},
226
- url="https://huggingface.co/datasets/wmt/wmt16/resolve/main-zip/translation-task/training-parallel-ep-v8.zip",
227
- path=("training-parallel-ep-v8/europarl-v8.{src}-en.{src}", "training-parallel-ep-v8/europarl-v8.{src}-en.en"),
228
- ),
229
- SubDataset(
230
- name="europarl_v9",
231
- target="en",
232
- sources={"cs", "de", "fi", "lt"},
233
- url="https://huggingface.co/datasets/wmt/europarl/resolve/main/v9/training/europarl-v9.{src}-en.tsv.gz",
234
- path="",
235
- ),
236
- SubDataset(
237
- name="gigafren",
238
- target="en",
239
- sources={"fr"},
240
- url="https://huggingface.co/datasets/wmt/wmt10/resolve/main-zip/training-giga-fren.zip",
241
- path=("giga-fren.release2.fixed.fr.gz", "giga-fren.release2.fixed.en.gz"),
242
- ),
243
- SubDataset(
244
- name="hindencorp_01",
245
- target="en",
246
- sources={"hi"},
247
- url="http://ufallab.ms.mff.cuni.cz/~bojar/hindencorp",
248
- manual_dl_files=["hindencorp0.1.gz"],
249
- path="",
250
- ),
251
- SubDataset(
252
- name="leta_v1",
253
- target="en",
254
- sources={"lv"},
255
- url="https://huggingface.co/datasets/wmt/wmt17/resolve/main-zip/translation-task/leta.v1.zip",
256
- path=("LETA-lv-en/leta.lv", "LETA-lv-en/leta.en"),
257
- ),
258
- SubDataset(
259
- name="multiun",
260
- target="en",
261
- sources={"es", "fr"},
262
- url="https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-un.zip",
263
- path=("un/undoc.2000.{src}-en.{src}", "un/undoc.2000.{src}-en.en"),
264
- ),
265
- SubDataset(
266
- name="newscommentary_v9",
267
- target="en",
268
- sources={"cs", "de", "fr", "ru"},
269
- url="https://huggingface.co/datasets/wmt/wmt14/resolve/main-zip/training-parallel-nc-v9.zip",
270
- path=("training/news-commentary-v9.{src}-en.{src}", "training/news-commentary-v9.{src}-en.en"),
271
- ),
272
- SubDataset(
273
- name="newscommentary_v10",
274
- target="en",
275
- sources={"cs", "de", "fr", "ru"},
276
- url="https://huggingface.co/datasets/wmt/wmt15/resolve/main-zip/training-parallel-nc-v10.zip",
277
- path=("news-commentary-v10.{src}-en.{src}", "news-commentary-v10.{src}-en.en"),
278
- ),
279
- SubDataset(
280
- name="newscommentary_v11",
281
- target="en",
282
- sources={"cs", "de", "ru"},
283
- url="https://huggingface.co/datasets/wmt/wmt16/resolve/main-zip/translation-task/training-parallel-nc-v11.zip",
284
- path=(
285
- "training-parallel-nc-v11/news-commentary-v11.{src}-en.{src}",
286
- "training-parallel-nc-v11/news-commentary-v11.{src}-en.en",
287
- ),
288
- ),
289
- SubDataset(
290
- name="newscommentary_v12",
291
- target="en",
292
- sources={"cs", "de", "ru", "zh"},
293
- url="https://huggingface.co/datasets/wmt/wmt17/resolve/main-zip/translation-task/training-parallel-nc-v12.zip",
294
- path=("training/news-commentary-v12.{src}-en.{src}", "training/news-commentary-v12.{src}-en.en"),
295
- ),
296
- SubDataset(
297
- name="newscommentary_v13",
298
- target="en",
299
- sources={"cs", "de", "ru", "zh"},
300
- url="https://huggingface.co/datasets/wmt/wmt18/resolve/main-zip/translation-task/training-parallel-nc-v13.zip",
301
- path=(
302
- "training-parallel-nc-v13/news-commentary-v13.{src}-en.{src}",
303
- "training-parallel-nc-v13/news-commentary-v13.{src}-en.en",
304
- ),
305
- ),
306
- SubDataset(
307
- name="newscommentary_v14",
308
- target="en", # fr-de pair in newscommentary_v14_frde
309
- sources={"cs", "de", "kk", "ru", "zh"},
310
- url="http://data.statmt.org/news-commentary/v14/training/news-commentary-v14.{0}-{1}.tsv.gz",
311
- path="",
312
- ),
313
- SubDataset(
314
- name="newscommentary_v14_frde",
315
- target="de",
316
- sources={"fr"},
317
- url="http://data.statmt.org/news-commentary/v14/training/news-commentary-v14.de-fr.tsv.gz",
318
- path="",
319
- ),
320
- SubDataset(
321
- name="onlinebooks_v1",
322
- target="en",
323
- sources={"lv"},
324
- url="https://huggingface.co/datasets/wmt/wmt17/resolve/main-zip/translation-task/books.lv-en.v1.zip",
325
- path=("farewell/farewell.lv", "farewell/farewell.en"),
326
- ),
327
- SubDataset(
328
- name="paracrawl_v1",
329
- target="en",
330
- sources={"cs", "de", "et", "fi", "ru"},
331
- url="https://s3.amazonaws.com/web-language-models/paracrawl/release1/paracrawl-release1.en-{src}.zipporah0-dedup-clean.tgz", # TODO(QL): use gzip for streaming
332
- path=(
333
- "paracrawl-release1.en-{src}.zipporah0-dedup-clean.{src}",
334
- "paracrawl-release1.en-{src}.zipporah0-dedup-clean.en",
335
- ),
336
- ),
337
- SubDataset(
338
- name="paracrawl_v1_ru",
339
- target="en",
340
- sources={"ru"},
341
- url="https://s3.amazonaws.com/web-language-models/paracrawl/release1/paracrawl-release1.en-ru.zipporah0-dedup-clean.tgz", # TODO(QL): use gzip for streaming
342
- path=(
343
- "paracrawl-release1.en-ru.zipporah0-dedup-clean.ru",
344
- "paracrawl-release1.en-ru.zipporah0-dedup-clean.en",
345
- ),
346
- ),
347
- SubDataset(
348
- name="paracrawl_v3",
349
- target="en", # fr-de pair in paracrawl_v3_frde
350
- sources={"cs", "de", "fi", "lt"},
351
- url="https://s3.amazonaws.com/web-language-models/paracrawl/release3/en-{src}.bicleaner07.tmx.gz",
352
- path="",
353
- ),
354
- SubDataset(
355
- name="paracrawl_v3_frde",
356
- target="de",
357
- sources={"fr"},
358
- url=(
359
- "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/fr-de/bitexts/de-fr.bicleaner07.de.gz",
360
- "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/fr-de/bitexts/de-fr.bicleaner07.fr.gz",
361
- ),
362
- path=("", ""),
363
- ),
364
- SubDataset(
365
- name="rapid_2016",
366
- target="en",
367
- sources={"de", "et", "fi"},
368
- url="https://huggingface.co/datasets/wmt/wmt18/resolve/main-zip/translation-task/rapid2016.zip",
369
- path=("rapid2016.{0}-{1}.{src}", "rapid2016.{0}-{1}.en"),
370
- ),
371
- SubDataset(
372
- name="rapid_2016_ltfi",
373
- target="en",
374
- sources={"fi", "lt"},
375
- url="https://tilde-model.s3-eu-west-1.amazonaws.com/rapid2016.en-{src}.tmx.zip",
376
- path="rapid2016.en-{src}.tmx",
377
- ),
378
- SubDataset(
379
- name="rapid_2019",
380
- target="en",
381
- sources={"de"},
382
- url="https://s3-eu-west-1.amazonaws.com/tilde-model/rapid2019.de-en.zip",
383
- path=("rapid2019.de-en.de", "rapid2019.de-en.en"),
384
- ),
385
- SubDataset(
386
- name="setimes_2",
387
- target="en",
388
- sources={"ro", "tr"},
389
- url="https://object.pouta.csc.fi/OPUS-SETIMES/v2/tmx/en-{src}.tmx.gz",
390
- path="",
391
- ),
392
- SubDataset(
393
- name="uncorpus_v1",
394
- target="en",
395
- sources={"ru", "zh"},
396
- url="https://huggingface.co/datasets/wmt/uncorpus/resolve/main-zip/UNv1.0.en-{src}.zip",
397
- path=("en-{src}/UNv1.0.en-{src}.{src}", "en-{src}/UNv1.0.en-{src}.en"),
398
- ),
399
- SubDataset(
400
- name="wikiheadlines_fi",
401
- target="en",
402
- sources={"fi"},
403
- url="https://huggingface.co/datasets/wmt/wmt15/resolve/main-zip/wiki-titles.zip",
404
- path="wiki/fi-en/titles.fi-en",
405
- ),
406
- SubDataset(
407
- name="wikiheadlines_hi",
408
- target="en",
409
- sources={"hi"},
410
- url="https://huggingface.co/datasets/wmt/wmt14/resolve/main-zip/wiki-titles.zip",
411
- path="wiki/hi-en/wiki-titles.hi-en",
412
- ),
413
- SubDataset(
414
- # Verified that wmt14 and wmt15 files are identical.
415
- name="wikiheadlines_ru",
416
- target="en",
417
- sources={"ru"},
418
- url="https://huggingface.co/datasets/wmt/wmt15/resolve/main-zip/wiki-titles.zip",
419
- path="wiki/ru-en/wiki.ru-en",
420
- ),
421
- SubDataset(
422
- name="wikititles_v1",
423
- target="en",
424
- sources={"cs", "de", "fi", "gu", "kk", "lt", "ru", "zh"},
425
- url="https://huggingface.co/datasets/wmt/wikititles/resolve/main/v1/wikititles-v1.{src}-en.tsv.gz",
426
- path="",
427
- ),
428
- SubDataset(
429
- name="yandexcorpus",
430
- target="en",
431
- sources={"ru"},
432
- url="https://translate.yandex.ru/corpus?lang=en",
433
- manual_dl_files=["1mcorpus.zip"],
434
- path=("corpus.en_ru.1m.ru", "corpus.en_ru.1m.en"),
435
- ),
436
- # pylint:enable=line-too-long
437
- ] + [
438
- SubDataset( # pylint:disable=g-complex-comprehension
439
- name=ss,
440
- target="en",
441
- sources={"zh"},
442
- url="https://huggingface.co/datasets/wmt/wmt18/resolve/main-zip/cwmt-wmt/%s.zip" % ss,
443
- path=("%s/*_c[hn].txt" % ss, "%s/*_en.txt" % ss),
444
- )
445
- for ss in CWMT_SUBSET_NAMES
446
- ]
447
-
448
- _DEV_SUBSETS = [
449
- SubDataset(
450
- name="euelections_dev2019",
451
- target="de",
452
- sources={"fr"},
453
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
454
- path=("dev/euelections_dev2019.fr-de.src.fr", "dev/euelections_dev2019.fr-de.tgt.de"),
455
- ),
456
- SubDataset(
457
- name="newsdev2014",
458
- target="en",
459
- sources={"hi"},
460
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
461
- path=("dev/newsdev2014.hi", "dev/newsdev2014.en"),
462
- ),
463
- SubDataset(
464
- name="newsdev2015",
465
- target="en",
466
- sources={"fi"},
467
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
468
- path=("dev/newsdev2015-fien-src.{src}.sgm", "dev/newsdev2015-fien-ref.en.sgm"),
469
- ),
470
- SubDataset(
471
- name="newsdiscussdev2015",
472
- target="en",
473
- sources={"ro", "tr"},
474
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
475
- path=("dev/newsdiscussdev2015-{src}en-src.{src}.sgm", "dev/newsdiscussdev2015-{src}en-ref.en.sgm"),
476
- ),
477
- SubDataset(
478
- name="newsdev2016",
479
- target="en",
480
- sources={"ro", "tr"},
481
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
482
- path=("dev/newsdev2016-{src}en-src.{src}.sgm", "dev/newsdev2016-{src}en-ref.en.sgm"),
483
- ),
484
- SubDataset(
485
- name="newsdev2017",
486
- target="en",
487
- sources={"lv", "zh"},
488
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
489
- path=("dev/newsdev2017-{src}en-src.{src}.sgm", "dev/newsdev2017-{src}en-ref.en.sgm"),
490
- ),
491
- SubDataset(
492
- name="newsdev2018",
493
- target="en",
494
- sources={"et"},
495
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
496
- path=("dev/newsdev2018-{src}en-src.{src}.sgm", "dev/newsdev2018-{src}en-ref.en.sgm"),
497
- ),
498
- SubDataset(
499
- name="newsdev2019",
500
- target="en",
501
- sources={"gu", "kk", "lt"},
502
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
503
- path=("dev/newsdev2019-{src}en-src.{src}.sgm", "dev/newsdev2019-{src}en-ref.en.sgm"),
504
- ),
505
- SubDataset(
506
- name="newsdiscussdev2015",
507
- target="en",
508
- sources={"fr"},
509
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
510
- path=("dev/newsdiscussdev2015-{src}en-src.{src}.sgm", "dev/newsdiscussdev2015-{src}en-ref.en.sgm"),
511
- ),
512
- SubDataset(
513
- name="newsdiscusstest2015",
514
- target="en",
515
- sources={"fr"},
516
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
517
- path=("dev/newsdiscusstest2015-{src}en-src.{src}.sgm", "dev/newsdiscusstest2015-{src}en-ref.en.sgm"),
518
- ),
519
- SubDataset(
520
- name="newssyscomb2009",
521
- target="en",
522
- sources={"cs", "de", "es", "fr"},
523
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
524
- path=("dev/newssyscomb2009.{src}", "dev/newssyscomb2009.en"),
525
- ),
526
- SubDataset(
527
- name="newstest2008",
528
- target="en",
529
- sources={"cs", "de", "es", "fr", "hu"},
530
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
531
- path=("dev/news-test2008.{src}", "dev/news-test2008.en"),
532
- ),
533
- SubDataset(
534
- name="newstest2009",
535
- target="en",
536
- sources={"cs", "de", "es", "fr"},
537
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
538
- path=("dev/newstest2009.{src}", "dev/newstest2009.en"),
539
- ),
540
- SubDataset(
541
- name="newstest2010",
542
- target="en",
543
- sources={"cs", "de", "es", "fr"},
544
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
545
- path=("dev/newstest2010.{src}", "dev/newstest2010.en"),
546
- ),
547
- SubDataset(
548
- name="newstest2011",
549
- target="en",
550
- sources={"cs", "de", "es", "fr"},
551
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
552
- path=("dev/newstest2011.{src}", "dev/newstest2011.en"),
553
- ),
554
- SubDataset(
555
- name="newstest2012",
556
- target="en",
557
- sources={"cs", "de", "es", "fr", "ru"},
558
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
559
- path=("dev/newstest2012.{src}", "dev/newstest2012.en"),
560
- ),
561
- SubDataset(
562
- name="newstest2013",
563
- target="en",
564
- sources={"cs", "de", "es", "fr", "ru"},
565
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
566
- path=("dev/newstest2013.{src}", "dev/newstest2013.en"),
567
- ),
568
- SubDataset(
569
- name="newstest2014",
570
- target="en",
571
- sources={"cs", "de", "es", "fr", "hi", "ru"},
572
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
573
- path=("dev/newstest2014-{src}en-src.{src}.sgm", "dev/newstest2014-{src}en-ref.en.sgm"),
574
- ),
575
- SubDataset(
576
- name="newstest2015",
577
- target="en",
578
- sources={"cs", "de", "fi", "ru"},
579
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
580
- path=("dev/newstest2015-{src}en-src.{src}.sgm", "dev/newstest2015-{src}en-ref.en.sgm"),
581
- ),
582
- SubDataset(
583
- name="newsdiscusstest2015",
584
- target="en",
585
- sources={"fr"},
586
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
587
- path=("dev/newsdiscusstest2015-{src}en-src.{src}.sgm", "dev/newsdiscusstest2015-{src}en-ref.en.sgm"),
588
- ),
589
- SubDataset(
590
- name="newstest2016",
591
- target="en",
592
- sources={"cs", "de", "fi", "ro", "ru", "tr"},
593
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
594
- path=("dev/newstest2016-{src}en-src.{src}.sgm", "dev/newstest2016-{src}en-ref.en.sgm"),
595
- ),
596
- SubDataset(
597
- name="newstestB2016",
598
- target="en",
599
- sources={"fi"},
600
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
601
- path=("dev/newstestB2016-enfi-ref.{src}.sgm", "dev/newstestB2016-enfi-src.en.sgm"),
602
- ),
603
- SubDataset(
604
- name="newstest2017",
605
- target="en",
606
- sources={"cs", "de", "fi", "lv", "ru", "tr", "zh"},
607
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
608
- path=("dev/newstest2017-{src}en-src.{src}.sgm", "dev/newstest2017-{src}en-ref.en.sgm"),
609
- ),
610
- SubDataset(
611
- name="newstestB2017",
612
- target="en",
613
- sources={"fi"},
614
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
615
- path=("dev/newstestB2017-fien-src.fi.sgm", "dev/newstestB2017-fien-ref.en.sgm"),
616
- ),
617
- SubDataset(
618
- name="newstest2018",
619
- target="en",
620
- sources={"cs", "de", "et", "fi", "ru", "tr", "zh"},
621
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
622
- path=("dev/newstest2018-{src}en-src.{src}.sgm", "dev/newstest2018-{src}en-ref.en.sgm"),
623
- ),
624
- ]
625
-
626
- DATASET_MAP = {dataset.name: dataset for dataset in _TRAIN_SUBSETS + _DEV_SUBSETS}
627
-
628
- _CZENG17_FILTER = SubDataset(
629
- name="czeng17_filter",
630
- target="en",
631
- sources={"cs"},
632
- url="http://ufal.mff.cuni.cz/czeng/download.php?f=convert_czeng16_to_17.pl.zip",
633
- path="convert_czeng16_to_17.pl",
634
- )
635
-
636
-
637
- class WmtConfig(datasets.BuilderConfig):
638
- """BuilderConfig for WMT."""
639
-
640
- def __init__(self, url=None, citation=None, description=None, language_pair=(None, None), subsets=None, **kwargs):
641
- """BuilderConfig for WMT.
642
-
643
- Args:
644
- url: The reference URL for the dataset.
645
- citation: The paper citation for the dataset.
646
- description: The description of the dataset.
647
- language_pair: pair of languages that will be used for translation. Should
648
- contain 2 letter coded strings. For example: ("en", "de").
649
- configuration for the `datasets.features.text.TextEncoder` used for the
650
- `datasets.features.text.Translation` features.
651
- subsets: Dict[split, list[str]]. List of the subset to use for each of the
652
- split. Note that WMT subclasses overwrite this parameter.
653
- **kwargs: keyword arguments forwarded to super.
654
- """
655
- name = "%s-%s" % (language_pair[0], language_pair[1])
656
- if "name" in kwargs: # Add name suffix for custom configs
657
- name += "." + kwargs.pop("name")
658
-
659
- super(WmtConfig, self).__init__(name=name, description=description, **kwargs)
660
-
661
- self.url = url or "http://www.statmt.org"
662
- self.citation = citation
663
- self.language_pair = language_pair
664
- self.subsets = subsets
665
-
666
- # TODO(PVP): remove when manual dir works
667
- # +++++++++++++++++++++
668
- if language_pair[1] in ["cs", "hi", "ru"]:
669
- assert NotImplementedError(f"The dataset for {language_pair[1]}-en is currently not fully supported.")
670
- # +++++++++++++++++++++
671
-
672
-
673
- class Wmt(datasets.GeneratorBasedBuilder):
674
- """WMT translation dataset."""
675
-
676
- BUILDER_CONFIG_CLASS = WmtConfig
677
-
678
- def __init__(self, *args, **kwargs):
679
- super(Wmt, self).__init__(*args, **kwargs)
680
-
681
- @property
682
- def _subsets(self):
683
- """Subsets that make up each split of the dataset."""
684
- raise NotImplementedError("This is a abstract method")
685
-
686
- @property
687
- def subsets(self):
688
- """Subsets that make up each split of the dataset for the language pair."""
689
- source, target = self.config.language_pair
690
- filtered_subsets = {}
691
- subsets = self._subsets if self.config.subsets is None else self.config.subsets
692
- for split, ss_names in subsets.items():
693
- filtered_subsets[split] = []
694
- for ss_name in ss_names:
695
- dataset = DATASET_MAP[ss_name]
696
- if dataset.target != target or source not in dataset.sources:
697
- logger.info("Skipping sub-dataset that does not include language pair: %s", ss_name)
698
- else:
699
- filtered_subsets[split].append(ss_name)
700
- logger.info("Using sub-datasets: %s", filtered_subsets)
701
- return filtered_subsets
702
-
703
- def _info(self):
704
- src, target = self.config.language_pair
705
- return datasets.DatasetInfo(
706
- description=_DESCRIPTION,
707
- features=datasets.Features(
708
- {"translation": datasets.features.Translation(languages=self.config.language_pair)}
709
- ),
710
- supervised_keys=(src, target),
711
- homepage=self.config.url,
712
- citation=self.config.citation,
713
- )
714
-
715
- def _vocab_text_gen(self, split_subsets, extraction_map, language):
716
- for _, ex in self._generate_examples(split_subsets, extraction_map, with_translation=False):
717
- yield ex[language]
718
-
719
- def _split_generators(self, dl_manager):
720
- source, _ = self.config.language_pair
721
- manual_paths_dict = {}
722
- urls_to_download = {}
723
- for ss_name in itertools.chain.from_iterable(self.subsets.values()):
724
- if ss_name == "czeng_17":
725
- # CzEng1.7 is CzEng1.6 with some blocks filtered out. We must download
726
- # the filtering script so we can parse out which blocks need to be
727
- # removed.
728
- urls_to_download[_CZENG17_FILTER.name] = _CZENG17_FILTER.get_url(source)
729
-
730
- # get dataset
731
- dataset = DATASET_MAP[ss_name]
732
- if dataset.get_manual_dl_files(source):
733
- # TODO(PVP): following two lines skip configs that are incomplete for now
734
- # +++++++++++++++++++++
735
- logger.info("Skipping {dataset.name} for now. Incomplete dataset for {self.config.name}")
736
- continue
737
- # +++++++++++++++++++++
738
-
739
- manual_dl_files = dataset.get_manual_dl_files(source)
740
- manual_paths = [
741
- os.path.join(os.path.abspath(os.path.expanduser(dl_manager.manual_dir)), fname)
742
- for fname in manual_dl_files
743
- ]
744
- assert all(
745
- os.path.exists(path) for path in manual_paths
746
- ), f"For {dataset.name}, you must manually download the following file(s) from {dataset.get_url(source)} and place them in {dl_manager.manual_dir}: {', '.join(manual_dl_files)}"
747
-
748
- # set manual path for correct subset
749
- manual_paths_dict[ss_name] = manual_paths
750
- else:
751
- urls_to_download[ss_name] = dataset.get_url(source)
752
-
753
- # Download and extract files from URLs.
754
- downloaded_files = dl_manager.download_and_extract(urls_to_download)
755
- # Extract manually downloaded files.
756
- manual_files = dl_manager.extract(manual_paths_dict)
757
- extraction_map = dict(downloaded_files, **manual_files)
758
-
759
- for language in self.config.language_pair:
760
- self._vocab_text_gen(self.subsets[datasets.Split.TRAIN], extraction_map, language)
761
-
762
- return [
763
- datasets.SplitGenerator( # pylint:disable=g-complex-comprehension
764
- name=split, gen_kwargs={"split_subsets": split_subsets, "extraction_map": extraction_map}
765
- )
766
- for split, split_subsets in self.subsets.items()
767
- ]
768
-
769
- def _generate_examples(self, split_subsets, extraction_map, with_translation=True):
770
- """Returns the examples in the raw (text) form."""
771
- source, _ = self.config.language_pair
772
-
773
- def _get_local_paths(dataset, extract_dirs):
774
- rel_paths = dataset.get_path(source)
775
- if len(extract_dirs) == 1:
776
- extract_dirs = extract_dirs * len(rel_paths)
777
- return [
778
- os.path.join(ex_dir, rel_path) if rel_path else ex_dir
779
- for ex_dir, rel_path in zip(extract_dirs, rel_paths)
780
- ]
781
-
782
- def _get_filenames(dataset):
783
- rel_paths = dataset.get_path(source)
784
- urls = dataset.get_url(source)
785
- if len(urls) == 1:
786
- urls = urls * len(rel_paths)
787
- return [rel_path if rel_path else os.path.basename(url) for url, rel_path in zip(urls, rel_paths)]
788
-
789
- for ss_name in split_subsets:
790
- # TODO(PVP) remove following five lines when manual data works
791
- # +++++++++++++++++++++
792
- dataset = DATASET_MAP[ss_name]
793
- source, _ = self.config.language_pair
794
- if dataset.get_manual_dl_files(source):
795
- logger.info(f"Skipping {dataset.name} for now. Incomplete dataset for {self.config.name}")
796
- continue
797
- # +++++++++++++++++++++
798
-
799
- logger.info("Generating examples from: %s", ss_name)
800
- dataset = DATASET_MAP[ss_name]
801
- extract_dirs = extraction_map[ss_name]
802
- files = _get_local_paths(dataset, extract_dirs)
803
- filenames = _get_filenames(dataset)
804
-
805
- sub_generator_args = tuple(files)
806
-
807
- if ss_name.startswith("czeng"):
808
- if ss_name.endswith("16pre"):
809
- sub_generator = functools.partial(_parse_tsv, language_pair=("en", "cs"))
810
- sub_generator_args += tuple(filenames)
811
- elif ss_name.endswith("17"):
812
- filter_path = _get_local_paths(_CZENG17_FILTER, extraction_map[_CZENG17_FILTER.name])[0]
813
- sub_generator = functools.partial(_parse_czeng, filter_path=filter_path)
814
- else:
815
- sub_generator = _parse_czeng
816
- elif ss_name == "hindencorp_01":
817
- sub_generator = _parse_hindencorp
818
- elif len(files) == 2:
819
- if ss_name.endswith("_frde"):
820
- sub_generator = _parse_frde_bitext
821
- else:
822
- sub_generator = _parse_parallel_sentences
823
- sub_generator_args += tuple(filenames)
824
- elif len(files) == 1:
825
- fname = filenames[0]
826
- # Note: Due to formatting used by `download_manager`, the file
827
- # extension may not be at the end of the file path.
828
- if ".tsv" in fname:
829
- sub_generator = _parse_tsv
830
- sub_generator_args += tuple(filenames)
831
- elif (
832
- ss_name.startswith("newscommentary_v14")
833
- or ss_name.startswith("europarl_v9")
834
- or ss_name.startswith("wikititles_v1")
835
- ):
836
- sub_generator = functools.partial(_parse_tsv, language_pair=self.config.language_pair)
837
- sub_generator_args += tuple(filenames)
838
- elif "tmx" in fname or ss_name.startswith("paracrawl_v3"):
839
- sub_generator = _parse_tmx
840
- elif ss_name.startswith("wikiheadlines"):
841
- sub_generator = _parse_wikiheadlines
842
- else:
843
- raise ValueError("Unsupported file format: %s" % fname)
844
- else:
845
- raise ValueError("Invalid number of files: %d" % len(files))
846
-
847
- for sub_key, ex in sub_generator(*sub_generator_args):
848
- if not all(ex.values()):
849
- continue
850
- # TODO(adarob): Add subset feature.
851
- # ex["subset"] = subset
852
- key = f"{ss_name}/{sub_key}"
853
- if with_translation is True:
854
- ex = {"translation": ex}
855
- yield key, ex
856
-
857
-
858
- def _parse_parallel_sentences(f1, f2, filename1, filename2):
859
- """Returns examples from parallel SGML or text files, which may be gzipped."""
860
-
861
- def _parse_text(path, original_filename):
862
- """Returns the sentences from a single text file, which may be gzipped."""
863
- split_path = original_filename.split(".")
864
-
865
- if split_path[-1] == "gz":
866
- lang = split_path[-2]
867
-
868
- def gen():
869
- with open(path, "rb") as f, gzip.GzipFile(fileobj=f) as g:
870
- for line in g:
871
- yield line.decode("utf-8").rstrip()
872
-
873
- return gen(), lang
874
-
875
- if split_path[-1] == "txt":
876
- # CWMT
877
- lang = split_path[-2].split("_")[-1]
878
- lang = "zh" if lang in ("ch", "cn", "c[hn]") else lang
879
- else:
880
- lang = split_path[-1]
881
-
882
- def gen():
883
- with open(path, "rb") as f:
884
- for line in f:
885
- yield line.decode("utf-8").rstrip()
886
-
887
- return gen(), lang
888
-
889
- def _parse_sgm(path, original_filename):
890
- """Returns sentences from a single SGML file."""
891
- lang = original_filename.split(".")[-2]
892
- # Note: We can't use the XML parser since some of the files are badly
893
- # formatted.
894
- seg_re = re.compile(r"<seg id=\"\d+\">(.*)</seg>")
895
-
896
- def gen():
897
- with open(path, encoding="utf-8") as f:
898
- for line in f:
899
- seg_match = re.match(seg_re, line)
900
- if seg_match:
901
- assert len(seg_match.groups()) == 1
902
- yield seg_match.groups()[0]
903
-
904
- return gen(), lang
905
-
906
- parse_file = _parse_sgm if os.path.basename(f1).endswith(".sgm") else _parse_text
907
-
908
- # Some datasets (e.g., CWMT) contain multiple parallel files specified with
909
- # a wildcard. We sort both sets to align them and parse them one by one.
910
- f1_files = sorted(glob.glob(f1))
911
- f2_files = sorted(glob.glob(f2))
912
-
913
- assert f1_files and f2_files, "No matching files found: %s, %s." % (f1, f2)
914
- assert len(f1_files) == len(f2_files), "Number of files do not match: %d vs %d for %s vs %s." % (
915
- len(f1_files),
916
- len(f2_files),
917
- f1,
918
- f2,
919
- )
920
-
921
- for f_id, (f1_i, f2_i) in enumerate(zip(sorted(f1_files), sorted(f2_files))):
922
- l1_sentences, l1 = parse_file(f1_i, filename1)
923
- l2_sentences, l2 = parse_file(f2_i, filename2)
924
-
925
- for line_id, (s1, s2) in enumerate(zip(l1_sentences, l2_sentences)):
926
- key = f"{f_id}/{line_id}"
927
- yield key, {l1: s1, l2: s2}
928
-
929
-
930
- def _parse_frde_bitext(fr_path, de_path):
931
- with open(fr_path, encoding="utf-8") as fr_f:
932
- with open(de_path, encoding="utf-8") as de_f:
933
- for line_id, (s1, s2) in enumerate(zip(fr_f, de_f)):
934
- yield line_id, {"fr": s1.rstrip(), "de": s2.rstrip()}
935
-
936
-
937
- def _parse_tmx(path):
938
- """Generates examples from TMX file."""
939
-
940
- def _get_tuv_lang(tuv):
941
- for k, v in tuv.items():
942
- if k.endswith("}lang"):
943
- return v
944
- raise AssertionError("Language not found in `tuv` attributes.")
945
-
946
- def _get_tuv_seg(tuv):
947
- segs = tuv.findall("seg")
948
- assert len(segs) == 1, "Invalid number of segments: %d" % len(segs)
949
- return segs[0].text
950
-
951
- with open(path, "rb") as f:
952
- # Workaround due to: https://github.com/tensorflow/tensorflow/issues/33563
953
- utf_f = codecs.getreader("utf-8")(f)
954
- for line_id, (_, elem) in enumerate(ElementTree.iterparse(utf_f)):
955
- if elem.tag == "tu":
956
- yield line_id, {_get_tuv_lang(tuv): _get_tuv_seg(tuv) for tuv in elem.iterfind("tuv")}
957
- elem.clear()
958
-
959
-
960
- def _parse_tsv(path, filename, language_pair=None):
961
- """Generates examples from TSV file."""
962
- if language_pair is None:
963
- lang_match = re.match(r".*\.([a-z][a-z])-([a-z][a-z])\.tsv", filename)
964
- assert lang_match is not None, "Invalid TSV filename: %s" % filename
965
- l1, l2 = lang_match.groups()
966
- else:
967
- l1, l2 = language_pair
968
- with open(path, encoding="utf-8") as f:
969
- for j, line in enumerate(f):
970
- cols = line.split("\t")
971
- if len(cols) != 2:
972
- logger.warning("Skipping line %d in TSV (%s) with %d != 2 columns.", j, path, len(cols))
973
- continue
974
- s1, s2 = cols
975
- yield j, {l1: s1.strip(), l2: s2.strip()}
976
-
977
-
978
- def _parse_wikiheadlines(path):
979
- """Generates examples from Wikiheadlines dataset file."""
980
- lang_match = re.match(r".*\.([a-z][a-z])-([a-z][a-z])$", path)
981
- assert lang_match is not None, "Invalid Wikiheadlines filename: %s" % path
982
- l1, l2 = lang_match.groups()
983
- with open(path, encoding="utf-8") as f:
984
- for line_id, line in enumerate(f):
985
- s1, s2 = line.split("|||")
986
- yield line_id, {l1: s1.strip(), l2: s2.strip()}
987
-
988
-
989
- def _parse_czeng(*paths, **kwargs):
990
- """Generates examples from CzEng v1.6, with optional filtering for v1.7."""
991
- filter_path = kwargs.get("filter_path", None)
992
- if filter_path:
993
- re_block = re.compile(r"^[^-]+-b(\d+)-\d\d[tde]")
994
- with open(filter_path, encoding="utf-8") as f:
995
- bad_blocks = {blk for blk in re.search(r"qw{([\s\d]*)}", f.read()).groups()[0].split()}
996
- logger.info("Loaded %d bad blocks to filter from CzEng v1.6 to make v1.7.", len(bad_blocks))
997
-
998
- for path in paths:
999
- for gz_path in sorted(glob.glob(path)):
1000
- with open(gz_path, "rb") as g, gzip.GzipFile(fileobj=g) as f:
1001
- filename = os.path.basename(gz_path)
1002
- for line_id, line in enumerate(f):
1003
- line = line.decode("utf-8") # required for py3
1004
- if not line.strip():
1005
- continue
1006
- id_, unused_score, cs, en = line.split("\t")
1007
- if filter_path:
1008
- block_match = re.match(re_block, id_)
1009
- if block_match and block_match.groups()[0] in bad_blocks:
1010
- continue
1011
- sub_key = f"{filename}/{line_id}"
1012
- yield sub_key, {
1013
- "cs": cs.strip(),
1014
- "en": en.strip(),
1015
- }
1016
-
1017
-
1018
- def _parse_hindencorp(path):
1019
- with open(path, encoding="utf-8") as f:
1020
- for line_id, line in enumerate(f):
1021
- split_line = line.split("\t")
1022
- if len(split_line) != 5:
1023
- logger.warning("Skipping invalid HindEnCorp line: %s", line)
1024
- continue
1025
- yield line_id, {"translation": {"en": split_line[3].strip(), "hi": split_line[4].strip()}}