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README.md

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----
-annotations_creators:
-- no-annotation
-language_creators:
-- found
-language:
-- cs
-- de
-- en
-- fi
-- fr
-- gu
-- kk
-- lt
-- ru
-- zh
-license:
-- unknown
-multilinguality:
-- translation
-size_categories:
-- 10M<n<100M
-source_datasets:
-- extended|europarl_bilingual
-- extended|news_commentary
-- extended|opus_paracrawl
-- extended|un_multi
-task_categories:
-- translation
-task_ids: []
-pretty_name: WMT19
-paperswithcode_id: null
-dataset_info:
-- config_name: cs-en
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - cs
-        - en
-  splits:
-  - name: train
-    num_bytes: 1314871994
-    num_examples: 7270695
-  - name: validation
-    num_bytes: 696229
-    num_examples: 2983
-  download_size: 2018537046
-  dataset_size: 1315568223
-- config_name: de-en
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - de
-        - en
-  splits:
-  - name: train
-    num_bytes: 8420967590
-    num_examples: 38690334
-  - name: validation
-    num_bytes: 757649
-    num_examples: 2998
-  download_size: 10422475109
-  dataset_size: 8421725239
-- config_name: fi-en
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - fi
-        - en
-  splits:
-  - name: train
-    num_bytes: 1422922267
-    num_examples: 6587448
-  - name: validation
-    num_bytes: 691841
-    num_examples: 3000
-  download_size: 1006124909
-  dataset_size: 1423614108
-- config_name: gu-en
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - gu
-        - en
-  splits:
-  - name: train
-    num_bytes: 590763
-    num_examples: 11670
-  - name: validation
-    num_bytes: 774621
-    num_examples: 1998
-  download_size: 38891457
-  dataset_size: 1365384
-- config_name: kk-en
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - kk
-        - en
-  splits:
-  - name: train
-    num_bytes: 9157438
-    num_examples: 126583
-  - name: validation
-    num_bytes: 846857
-    num_examples: 2066
-  download_size: 41558315
-  dataset_size: 10004295
-- config_name: lt-en
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - lt
-        - en
-  splits:
-  - name: train
-    num_bytes: 513084361
-    num_examples: 2344893
-  - name: validation
-    num_bytes: 541953
-    num_examples: 2000
-  download_size: 411309952
-  dataset_size: 513626314
-- config_name: ru-en
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - ru
-        - en
-  splits:
-  - name: train
-    num_bytes: 13721377178
-    num_examples: 37492126
-  - name: validation
-    num_bytes: 1085596
-    num_examples: 3000
-  download_size: 4134147853
-  dataset_size: 13722462774
-- config_name: zh-en
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - zh
-        - en
-  splits:
-  - name: train
-    num_bytes: 5584359748
-    num_examples: 25984574
-  - name: validation
-    num_bytes: 1107522
-    num_examples: 3981
-  download_size: 2195879129
-  dataset_size: 5585467270
-- config_name: fr-de
-  features:
-  - name: translation
-    dtype:
-      translation:
-        languages:
-        - fr
-        - de
-  splits:
-  - name: train
-    num_bytes: 2358413485
-    num_examples: 9824476
-  - name: validation
-    num_bytes: 441426
-    num_examples: 1512
-  download_size: 757345846
-  dataset_size: 2358854911
----
-
-# Dataset Card for "wmt19"
-
-## Table of Contents
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
-  - [Languages](#languages)
-- [Dataset Structure](#dataset-structure)
-  - [Data Instances](#data-instances)
-  - [Data Fields](#data-fields)
-  - [Data Splits](#data-splits)
-- [Dataset Creation](#dataset-creation)
-  - [Curation Rationale](#curation-rationale)
-  - [Source Data](#source-data)
-  - [Annotations](#annotations)
-  - [Personal and Sensitive Information](#personal-and-sensitive-information)
-- [Considerations for Using the Data](#considerations-for-using-the-data)
-  - [Social Impact of Dataset](#social-impact-of-dataset)
-  - [Discussion of Biases](#discussion-of-biases)
-  - [Other Known Limitations](#other-known-limitations)
-- [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
-  - [Licensing Information](#licensing-information)
-  - [Citation Information](#citation-information)
-  - [Contributions](#contributions)
-
-## Dataset Description
-
-- **Homepage:** [http://www.statmt.org/wmt19/translation-task.html](http://www.statmt.org/wmt19/translation-task.html)
-- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-- **Size of downloaded dataset files:** 1924.57 MB
-- **Size of the generated dataset:** 1254.62 MB
-- **Total amount of disk used:** 3179.19 MB
-
-### Dataset Summary
-
-<div class="course-tip course-tip-orange bg-gradient-to-br dark:bg-gradient-to-r before:border-orange-500 dark:before:border-orange-800 from-orange-50 dark:from-gray-900 to-white dark:to-gray-950 border border-orange-50 text-orange-700 dark:text-gray-400">
-  <p><b>Warning:</b> There are issues with the Common Crawl corpus data (<a href="https://www.statmt.org/wmt13/training-parallel-commoncrawl.tgz">training-parallel-commoncrawl.tgz</a>):</p>
-  <ul>
-    <li>Non-English files contain many English sentences.</li>
-    <li>Their "parallel" sentences in English are not aligned: they are uncorrelated with their counterpart.</li>
-  </ul>
-  <p>We have contacted the WMT organizers.</p>
-</div>
-
-Translation dataset based on the data from statmt.org.
-
-Versions exist for different years using a combination of data
-sources. The base `wmt` allows you to create a custom dataset by choosing
-your own data/language pair. This can be done as follows:
-
-```python
-from datasets import inspect_dataset, load_dataset_builder
-
-inspect_dataset("wmt19", "path/to/scripts")
-builder = load_dataset_builder(
-    "path/to/scripts/wmt_utils.py",
-    language_pair=("fr", "de"),
-    subsets={
-        datasets.Split.TRAIN: ["commoncrawl_frde"],
-        datasets.Split.VALIDATION: ["euelections_dev2019"],
-    },
-)
-
-# Standard version
-builder.download_and_prepare()
-ds = builder.as_dataset()
-
-# Streamable version
-ds = builder.as_streaming_dataset()
-```
-
-### Supported Tasks and Leaderboards
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Languages
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-## Dataset Structure
-
-### Data Instances
-
-#### cs-en
-
-- **Size of downloaded dataset files:** 1924.57 MB
-- **Size of the generated dataset:** 1254.62 MB
-- **Total amount of disk used:** 3179.19 MB
-
-An example of 'validation' looks as follows.
-```
-
-```
-
-### Data Fields
-
-The data fields are the same among all splits.
-
-#### cs-en
-- `translation`: a multilingual `string` variable, with possible languages including `cs`, `en`.
-
-### Data Splits
-
-|name | train |validation|
-|-----|------:|---------:|
-|cs-en|7270695|      2983|
-
-## Dataset Creation
-
-### Curation Rationale
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Source Data
-
-#### Initial Data Collection and Normalization
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-#### Who are the source language producers?
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Annotations
-
-#### Annotation process
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-#### Who are the annotators?
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Personal and Sensitive Information
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Discussion of Biases
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Other Known Limitations
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-## Additional Information
-
-### Dataset Curators
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Licensing Information
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Citation Information
-
-```
-
-@ONLINE {wmt19translate,
-    author = "Wikimedia Foundation",
-    title  = "ACL 2019 Fourth Conference on Machine Translation (WMT19), Shared Task: Machine Translation of News",
-    url    = "http://www.statmt.org/wmt19/translation-task.html"
-}
-
-```
-
-
-### Contributions
-
-Thanks to [@patrickvonplaten](https://github.com/patrickvonplaten), [@mariamabarham](https://github.com/mariamabarham), [@thomwolf](https://github.com/thomwolf) for adding this dataset.

dataset_infos.json

@@ -1 +0,0 @@
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The base `wmt_translate` allows you to create your own config to choose\nyour own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.\n\n```\nconfig = datasets.wmt.WmtConfig(\n    version=\"0.0.1\",\n    language_pair=(\"fr\", \"de\"),\n    subsets={\n        datasets.Split.TRAIN: [\"commoncrawl_frde\"],\n        datasets.Split.VALIDATION: [\"euelections_dev2019\"],\n    },\n)\nbuilder = datasets.builder(\"wmt_translate\", config=config)\n```\n\n", "citation": "\n@ONLINE {wmt19translate,\n    author = {Wikimedia Foundation},\n    title  = {ACL 2019 Fourth Conference on Machine Translation (WMT19), Shared Task: Machine Translation of News},\n    url    = {http://www.statmt.org/wmt19/translation-task.html}\n}\n", "homepage": "http://www.statmt.org/wmt19/translation-task.html", "license": "", "features": {"translation": {"languages": ["cs", "en"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": {"input": "cs", "output": "en"}, "task_templates": null, "builder_name": "wmt19", "config_name": "cs-en", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1314871994, "num_examples": 7270695, "dataset_name": "wmt19"}, "validation": {"name": "validation", "num_bytes": 696229, "num_examples": 2983, "dataset_name": "wmt19"}}, "download_checksums": {"https://huggingface.co/datasets/wmt/europarl/resolve/main/v9/training/europarl-v9.cs-en.tsv.gz": {"num_bytes": 68176874, "checksum": "e5e46de957439cf14e5048fc4127656d91315646822f2ac6c0193b5758617f60"}, "https://s3.amazonaws.com/web-language-models/paracrawl/release3/en-cs.bicleaner07.tmx.gz": {"num_bytes": 957135146, "checksum": "404bd17f9988f74f6544f7f9762bfbc4e52f7532779c28187e34dc8a5176960e"}, "https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-commoncrawl.zip": {"num_bytes": 918734483, "checksum": "5ffe980072ea29adfd84568d099bea366d9f72772b988e670794ae851b4e5627"}, "http://data.statmt.org/news-commentary/v14/training/news-commentary-v14.cs-en.tsv.gz": {"num_bytes": 28119465, "checksum": "b0ef38b810bc67811eb908080243e0211062c26a7a71cc05996c96ea6c55e0ff"}, "http://ufal.mff.cuni.cz/czeng/download.php?f=convert_czeng16_to_17.pl.zip": {"num_bytes": 2544381, "checksum": "e66466e00aecd392daaf547275590a9264bbc6aed70118c5c7cfd6946daf24ac"}, "https://huggingface.co/datasets/wmt/wikititles/resolve/main/v1/wikititles-v1.cs-en.tsv.gz": {"num_bytes": 5112423, "checksum": "54c9899b3cf897aaa520645436843d57e36ba9cce22f2c544a63a62493e18002"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip": {"num_bytes": 38714274, "checksum": "d796e363740fdc4261aa6f5a3d2f8223e3adaee7d737b7724863325b8956dfd1"}}, "download_size": 2018537046, "post_processing_size": null, "dataset_size": 1315568223, "size_in_bytes": 3334105269}, "de-en": {"description": "Translate dataset based on the data from statmt.org.\n\nVersions exists for the different years using a combination of multiple data\nsources. The base `wmt_translate` allows you to create your own config to choose\nyour own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.\n\n```\nconfig = datasets.wmt.WmtConfig(\n    version=\"0.0.1\",\n    language_pair=(\"fr\", \"de\"),\n    subsets={\n        datasets.Split.TRAIN: [\"commoncrawl_frde\"],\n        datasets.Split.VALIDATION: [\"euelections_dev2019\"],\n    },\n)\nbuilder = datasets.builder(\"wmt_translate\", config=config)\n```\n\n", "citation": "\n@ONLINE {wmt19translate,\n    author = {Wikimedia Foundation},\n    title  = {ACL 2019 Fourth Conference on Machine Translation (WMT19), Shared Task: Machine Translation of News},\n    url    = {http://www.statmt.org/wmt19/translation-task.html}\n}\n", "homepage": "http://www.statmt.org/wmt19/translation-task.html", "license": "", "features": {"translation": {"languages": ["de", "en"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": {"input": "de", "output": "en"}, "task_templates": null, "builder_name": "wmt19", "config_name": "de-en", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 8420967590, "num_examples": 38690334, "dataset_name": "wmt19"}, "validation": {"name": "validation", "num_bytes": 757649, "num_examples": 2998, "dataset_name": "wmt19"}}, "download_checksums": {"https://huggingface.co/datasets/wmt/europarl/resolve/main/v9/training/europarl-v9.de-en.tsv.gz": {"num_bytes": 204454328, "checksum": "c2aef75d81bf06b22e4a9237319c1d53ba9668a13cb155c6b1361182cd3abc84"}, "https://s3.amazonaws.com/web-language-models/paracrawl/release3/en-de.bicleaner07.tmx.gz": {"num_bytes": 9091373722, "checksum": "fbeef288e4f1d294534be3afbf43469cf59938553436108d717873c1c50d34c7"}, "https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-commoncrawl.zip": {"num_bytes": 918734483, "checksum": "5ffe980072ea29adfd84568d099bea366d9f72772b988e670794ae851b4e5627"}, "http://data.statmt.org/news-commentary/v14/training/news-commentary-v14.de-en.tsv.gz": {"num_bytes": 39390551, "checksum": "8aaa98a77d38bd39dcbdbcb775f3b6c633700e4c10fd915cf3dc6b9bfd0f2dca"}, "https://huggingface.co/datasets/wmt/wikititles/resolve/main/v1/wikititles-v1.de-en.tsv.gz": {"num_bytes": 17919359, "checksum": "24b0222ee87b6b8b3142c92f1b6f3c49374503fb066c46f190f00bf717a67102"}, "https://s3-eu-west-1.amazonaws.com/tilde-model/rapid2019.de-en.zip": {"num_bytes": 111888392, "checksum": "ed5a10e57092715020334b918f6e114e5b6c7206bee3e956f2a1e2937c59c2e7"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip": {"num_bytes": 38714274, "checksum": "d796e363740fdc4261aa6f5a3d2f8223e3adaee7d737b7724863325b8956dfd1"}}, "download_size": 10422475109, "post_processing_size": null, "dataset_size": 8421725239, "size_in_bytes": 18844200348}, "fi-en": {"description": "Translate dataset based on the data from statmt.org.\n\nVersions exists for the different years using a combination of multiple data\nsources. The base `wmt_translate` allows you to create your own config to choose\nyour own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.\n\n```\nconfig = datasets.wmt.WmtConfig(\n    version=\"0.0.1\",\n    language_pair=(\"fr\", \"de\"),\n    subsets={\n        datasets.Split.TRAIN: [\"commoncrawl_frde\"],\n        datasets.Split.VALIDATION: [\"euelections_dev2019\"],\n    },\n)\nbuilder = datasets.builder(\"wmt_translate\", config=config)\n```\n\n", "citation": "\n@ONLINE {wmt19translate,\n    author = {Wikimedia Foundation},\n    title  = {ACL 2019 Fourth Conference on Machine Translation (WMT19), Shared Task: Machine Translation of News},\n    url    = {http://www.statmt.org/wmt19/translation-task.html}\n}\n", "homepage": "http://www.statmt.org/wmt19/translation-task.html", "license": "", "features": {"translation": {"languages": ["fi", "en"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": {"input": "fi", "output": "en"}, "task_templates": null, "builder_name": "wmt19", "config_name": "fi-en", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1422922267, "num_examples": 6587448, "dataset_name": "wmt19"}, "validation": {"name": "validation", "num_bytes": 691841, "num_examples": 3000, "dataset_name": "wmt19"}}, "download_checksums": {"https://huggingface.co/datasets/wmt/europarl/resolve/main/v9/training/europarl-v9.fi-en.tsv.gz": {"num_bytes": 194574376, "checksum": "6bd65e497db4cc783b08f8be62aaa4b85c67c1e260a09e785cef77ff9e4488e8"}, "https://s3.amazonaws.com/web-language-models/paracrawl/release3/en-fi.bicleaner07.tmx.gz": {"num_bytes": 726455593, "checksum": "d7741612d6d82b9479819b1acc1149343c5bed7d4953f982e8889f2156a8bf17"}, "https://huggingface.co/datasets/wmt/wikititles/resolve/main/v1/wikititles-v1.fi-en.tsv.gz": {"num_bytes": 5101486, "checksum": "01906ddfc88b20039939e69652c5ba9b335c4671be5131c00d76ec0420760fad"}, "https://tilde-model.s3-eu-west-1.amazonaws.com/rapid2016.en-fi.tmx.zip": {"num_bytes": 41279180, "checksum": "2a3ad1343cded48241b8ed38db9a963d89f924eb46429f9c3eace56b1f56ba4e"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip": {"num_bytes": 38714274, "checksum": "d796e363740fdc4261aa6f5a3d2f8223e3adaee7d737b7724863325b8956dfd1"}}, "download_size": 1006124909, "post_processing_size": null, "dataset_size": 1423614108, "size_in_bytes": 2429739017}, "gu-en": {"description": "Translate dataset based on the data from statmt.org.\n\nVersions exists for the different years using a combination of multiple data\nsources. The base `wmt_translate` allows you to create your own config to choose\nyour own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.\n\n```\nconfig = datasets.wmt.WmtConfig(\n    version=\"0.0.1\",\n    language_pair=(\"fr\", \"de\"),\n    subsets={\n        datasets.Split.TRAIN: [\"commoncrawl_frde\"],\n        datasets.Split.VALIDATION: [\"euelections_dev2019\"],\n    },\n)\nbuilder = datasets.builder(\"wmt_translate\", config=config)\n```\n\n", "citation": "\n@ONLINE {wmt19translate,\n    author = {Wikimedia Foundation},\n    title  = {ACL 2019 Fourth Conference on Machine Translation (WMT19), Shared Task: Machine Translation of News},\n    url    = {http://www.statmt.org/wmt19/translation-task.html}\n}\n", "homepage": "http://www.statmt.org/wmt19/translation-task.html", "license": "", "features": {"translation": {"languages": ["gu", "en"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": {"input": "gu", "output": "en"}, "task_templates": null, "builder_name": "wmt19", "config_name": "gu-en", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 590763, "num_examples": 11670, "dataset_name": "wmt19"}, "validation": {"name": "validation", "num_bytes": 774621, "num_examples": 1998, "dataset_name": "wmt19"}}, "download_checksums": {"https://huggingface.co/datasets/wmt/wikititles/resolve/main/v1/wikititles-v1.gu-en.tsv.gz": {"num_bytes": 177183, "checksum": "d07da4ff7e648e1e1bc3ac1303cd7c51df15704a13b8e6ce7ed46e938ef4ae8d"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip": {"num_bytes": 38714274, "checksum": "d796e363740fdc4261aa6f5a3d2f8223e3adaee7d737b7724863325b8956dfd1"}}, "download_size": 38891457, "post_processing_size": null, "dataset_size": 1365384, "size_in_bytes": 40256841}, "kk-en": {"description": "Translate dataset based on the data from statmt.org.\n\nVersions exists for the different years using a combination of multiple data\nsources. The base `wmt_translate` allows you to create your own config to choose\nyour own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.\n\n```\nconfig = datasets.wmt.WmtConfig(\n    version=\"0.0.1\",\n    language_pair=(\"fr\", \"de\"),\n    subsets={\n        datasets.Split.TRAIN: [\"commoncrawl_frde\"],\n        datasets.Split.VALIDATION: [\"euelections_dev2019\"],\n    },\n)\nbuilder = datasets.builder(\"wmt_translate\", config=config)\n```\n\n", "citation": "\n@ONLINE {wmt19translate,\n    author = {Wikimedia Foundation},\n    title  = {ACL 2019 Fourth Conference on Machine Translation (WMT19), Shared Task: Machine Translation of News},\n    url    = {http://www.statmt.org/wmt19/translation-task.html}\n}\n", "homepage": "http://www.statmt.org/wmt19/translation-task.html", "license": "", "features": {"translation": {"languages": ["kk", "en"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": {"input": "kk", "output": "en"}, "task_templates": null, "builder_name": "wmt19", "config_name": "kk-en", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 9157438, "num_examples": 126583, "dataset_name": "wmt19"}, "validation": {"name": "validation", "num_bytes": 846857, "num_examples": 2066, "dataset_name": "wmt19"}}, "download_checksums": {"http://data.statmt.org/news-commentary/v14/training/news-commentary-v14.en-kk.tsv.gz": {"num_bytes": 1269004, "checksum": "bc0fdd1dd040c53409ace60c019a8a58450a36f128bc1e4263fcb5d4fc1bf0cb"}, "https://huggingface.co/datasets/wmt/wikititles/resolve/main/v1/wikititles-v1.kk-en.tsv.gz": {"num_bytes": 1575037, "checksum": "6117eb91ca5538298c15fb366fb7f15e5294c12ef7993f249f307f93c52ae504"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip": {"num_bytes": 38714274, "checksum": "d796e363740fdc4261aa6f5a3d2f8223e3adaee7d737b7724863325b8956dfd1"}}, "download_size": 41558315, "post_processing_size": null, "dataset_size": 10004295, "size_in_bytes": 51562610}, "lt-en": {"description": "Translate dataset based on the data from statmt.org.\n\nVersions exists for the different years using a combination of multiple data\nsources. 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The base `wmt_translate` allows you to create your own config to choose\nyour own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.\n\n```\nconfig = datasets.wmt.WmtConfig(\n    version=\"0.0.1\",\n    language_pair=(\"fr\", \"de\"),\n    subsets={\n        datasets.Split.TRAIN: [\"commoncrawl_frde\"],\n        datasets.Split.VALIDATION: [\"euelections_dev2019\"],\n    },\n)\nbuilder = datasets.builder(\"wmt_translate\", config=config)\n```\n\n", "citation": "\n@ONLINE {wmt19translate,\n    author = {Wikimedia Foundation},\n    title  = {ACL 2019 Fourth Conference on Machine Translation (WMT19), Shared Task: Machine Translation of News},\n    url    = {http://www.statmt.org/wmt19/translation-task.html}\n}\n", "homepage": "http://www.statmt.org/wmt19/translation-task.html", "license": "", "features": {"translation": {"languages": ["ru", "en"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": {"input": "ru", "output": "en"}, "task_templates": null, "builder_name": "wmt19", "config_name": "ru-en", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 13721377178, "num_examples": 37492126, "dataset_name": "wmt19"}, "validation": {"name": "validation", "num_bytes": 1085596, "num_examples": 3000, "dataset_name": "wmt19"}}, "download_checksums": {"https://s3.amazonaws.com/web-language-models/paracrawl/release1/paracrawl-release1.en-ru.zipporah0-dedup-clean.tgz": {"num_bytes": 667981874, "checksum": "d4902407ef462034e88fbf5d8712a11c4b32a6e0e82d3a1b4f42a6f33d94f3c0"}, "https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-commoncrawl.zip": {"num_bytes": 918734483, "checksum": "5ffe980072ea29adfd84568d099bea366d9f72772b988e670794ae851b4e5627"}, "http://data.statmt.org/news-commentary/v14/training/news-commentary-v14.en-ru.tsv.gz": {"num_bytes": 41411245, "checksum": "09aef10a0bb51104622ff6852cdf4f693b5906de970156b4e8db1e64ec55340c"}, "https://huggingface.co/datasets/wmt/wikititles/resolve/main/v1/wikititles-v1.ru-en.tsv.gz": {"num_bytes": 20299017, "checksum": "5da4f340b3ac684dca016bb5fc0730b00fc9808f0a4891a6d745aaa686a600e4"}, "https://huggingface.co/datasets/wmt/uncorpus/resolve/main-zip/UNv1.0.en-ru.zip": {"num_bytes": 2447006960, "checksum": "72c2670fa6aadb36d541cba91cd26b9da291a976bf1a2748177a57baf8261f4c"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip": {"num_bytes": 38714274, "checksum": "d796e363740fdc4261aa6f5a3d2f8223e3adaee7d737b7724863325b8956dfd1"}}, "download_size": 4134147853, "post_processing_size": null, "dataset_size": 13722462774, "size_in_bytes": 17856610627}, "zh-en": {"description": "Translate dataset based on the data from statmt.org.\n\nVersions exists for the different years using a combination of multiple data\nsources. The base `wmt_translate` allows you to create your own config to choose\nyour own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.\n\n```\nconfig = datasets.wmt.WmtConfig(\n    version=\"0.0.1\",\n    language_pair=(\"fr\", \"de\"),\n    subsets={\n        datasets.Split.TRAIN: [\"commoncrawl_frde\"],\n        datasets.Split.VALIDATION: [\"euelections_dev2019\"],\n    },\n)\nbuilder = datasets.builder(\"wmt_translate\", config=config)\n```\n\n", "citation": "\n@ONLINE {wmt19translate,\n    author = {Wikimedia Foundation},\n    title  = {ACL 2019 Fourth Conference on Machine Translation (WMT19), Shared Task: Machine Translation of News},\n    url    = {http://www.statmt.org/wmt19/translation-task.html}\n}\n", "homepage": "http://www.statmt.org/wmt19/translation-task.html", "license": "", "features": {"translation": {"languages": ["zh", "en"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": {"input": "zh", "output": "en"}, "task_templates": null, "builder_name": "wmt19", "config_name": "zh-en", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 5584359748, "num_examples": 25984574, "dataset_name": "wmt19"}, "validation": {"name": "validation", "num_bytes": 1107522, "num_examples": 3981, "dataset_name": "wmt19"}}, "download_checksums": {"http://data.statmt.org/news-commentary/v14/training/news-commentary-v14.en-zh.tsv.gz": {"num_bytes": 36696769, "checksum": "fc9cc3f28ad62872d8eece1dffb1148f972baf6621bc87ba049a3ae0aab4025b"}, "https://huggingface.co/datasets/wmt/wikititles/resolve/main/v1/wikititles-v1.zh-en.tsv.gz": {"num_bytes": 12974754, "checksum": "78a8d371c0c1de14786bcbaaa08049d7f77ed58ecef3bc95a305ad17944f1fcb"}, "https://huggingface.co/datasets/wmt/uncorpus/resolve/main-zip/UNv1.0.en-zh.zip": {"num_bytes": 1385832125, "checksum": "97f5ce0892084cdbb2332b52ffcc0299a649ba0a43712d921575fe2b7edfb4b4"}, "https://huggingface.co/datasets/wmt/wmt18/resolve/main/cwmt-wmt/casia2015.zip": {"num_bytes": 98159063, "checksum": "c939f1528f96c419e9bbffb9caad869616a969e7704ffac896e245a02aff59a9"}, "https://huggingface.co/datasets/wmt/wmt18/resolve/main/cwmt-wmt/casict2011.zip": {"num_bytes": 166957775, "checksum": "606adc0ccc5d8fc7c47f8589991286616342a1a379a571ce3038918731ae0182"}, "https://huggingface.co/datasets/wmt/wmt18/resolve/main/cwmt-wmt/casict2015.zip": {"num_bytes": 106836569, "checksum": "eef8e25b297c1aff12ab24719247d3588e756d7a4e2c30d4d34fcb4d05ab1050"}, "https://huggingface.co/datasets/wmt/wmt18/resolve/main/cwmt-wmt/datum2015.zip": {"num_bytes": 100118018, "checksum": "654afce6731485c40ce856514ab80cd2bfd836126bcaf48cdb911ebc32b021a4"}, "https://huggingface.co/datasets/wmt/wmt18/resolve/main/cwmt-wmt/datum2017.zip": {"num_bytes": 99278067, "checksum": "737455c139596f4abf3b1da73bc38932b3ef9534549328eff47d867e29950ed2"}, "https://huggingface.co/datasets/wmt/wmt18/resolve/main/cwmt-wmt/neu2017.zip": {"num_bytes": 150311715, "checksum": "5c5ea9ac5cbc43c974bd53796a3a29829800865b6398b52cda0a3854cb0d2e03"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip": {"num_bytes": 38714274, "checksum": "d796e363740fdc4261aa6f5a3d2f8223e3adaee7d737b7724863325b8956dfd1"}}, "download_size": 2195879129, "post_processing_size": null, "dataset_size": 5585467270, "size_in_bytes": 7781346399}, "fr-de": {"description": "Translate dataset based on the data from statmt.org.\n\nVersions exists for the different years using a combination of multiple data\nsources. The base `wmt_translate` allows you to create your own config to choose\nyour own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.\n\n```\nconfig = datasets.wmt.WmtConfig(\n    version=\"0.0.1\",\n    language_pair=(\"fr\", \"de\"),\n    subsets={\n        datasets.Split.TRAIN: [\"commoncrawl_frde\"],\n        datasets.Split.VALIDATION: [\"euelections_dev2019\"],\n    },\n)\nbuilder = datasets.builder(\"wmt_translate\", config=config)\n```\n\n", "citation": "\n@ONLINE {wmt19translate,\n    author = {Wikimedia Foundation},\n    title  = {ACL 2019 Fourth Conference on Machine Translation (WMT19), Shared Task: Machine Translation of News},\n    url    = {http://www.statmt.org/wmt19/translation-task.html}\n}\n", "homepage": "http://www.statmt.org/wmt19/translation-task.html", "license": "", "features": {"translation": {"languages": ["fr", "de"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": {"input": "fr", "output": "de"}, "task_templates": null, "builder_name": "wmt19", "config_name": "fr-de", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2358413485, "num_examples": 9824476, "dataset_name": "wmt19"}, "validation": {"name": "validation", "num_bytes": 441426, "num_examples": 1512, "dataset_name": "wmt19"}}, "download_checksums": {"https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/fr-de/bitexts/europarl-v7.fr.gz": {"num_bytes": 93157785, "checksum": "a065d9e973cd126f0fe72437e2ae03af0cb4b102d51f711e7985034daf60de96"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/fr-de/bitexts/europarl-v7.de.gz": {"num_bytes": 97417749, "checksum": "6850fac194d2cf74a732588ac78b04488a63b79c5481779e77cbab7d0e655a1e"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/fr-de/bitexts/de-fr.bicleaner07.de.gz": {"num_bytes": 216045091, "checksum": "cc71eb1f4772acc12314827d91fbaea6a5a73678b97b1a699fb9505430c23bc8"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/fr-de/bitexts/de-fr.bicleaner07.fr.gz": {"num_bytes": 212226219, "checksum": "c5c6c94c8c0d574fa93a8ed57f5a43baf2cf77844bb77bc0d81dbbae77444e52"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/fr-de/bitexts/commoncrawl.fr.gz": {"num_bytes": 32607032, "checksum": "cf4e89b6a8058243d7d91a978624b124f1e3a47dea4e124a7e25085e2455a5a6"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/fr-de/bitexts/commoncrawl.de.gz": {"num_bytes": 33273148, "checksum": "1bbbc4502130dd8152286cb0b8cadeeaeb4eff5b3f8cf1e710f6c023733cf5da"}, "http://data.statmt.org/news-commentary/v14/training/news-commentary-v14.de-fr.tsv.gz": {"num_bytes": 33904548, "checksum": "31a7735fe2ae6d6841847fdebb5aed03d5da1c15500695154d3c35d40c29cb09"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip": {"num_bytes": 38714274, "checksum": "d796e363740fdc4261aa6f5a3d2f8223e3adaee7d737b7724863325b8956dfd1"}}, "download_size": 757345846, "post_processing_size": null, "dataset_size": 2358854911, "size_in_bytes": 3116200757}}

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-# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
-#
-# 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.
-
-# Lint as: python3
-"""WMT19: Translate dataset."""
-
-import datasets
-
-from .wmt_utils import CWMT_SUBSET_NAMES, Wmt, WmtConfig
-
-
-_URL = "http://www.statmt.org/wmt19/translation-task.html"
-# TODO(adarob): Update with citation of overview paper once it is published.
-_CITATION = """
-@ONLINE {wmt19translate,
-    author = {Wikimedia Foundation},
-    title  = {ACL 2019 Fourth Conference on Machine Translation (WMT19), Shared Task: Machine Translation of News},
-    url    = {http://www.statmt.org/wmt19/translation-task.html}
-}
-"""
-
-_LANGUAGE_PAIRS = [(lang, "en") for lang in ["cs", "de", "fi", "gu", "kk", "lt", "ru", "zh"]] + [("fr", "de")]
-
-
-class Wmt19(Wmt):
-    """WMT 19 translation datasets for {(xx, "en")} + ("fr", "de") pairs."""
-
-    # Version history:
-    # 1.0.0: S3 (new shuffling, sharding and slicing mechanism).
-    BUILDER_CONFIGS = [
-        WmtConfig(  # pylint:disable=g-complex-comprehension
-            description="WMT 2019 %s-%s translation task dataset." % (l1, l2),
-            url=_URL,
-            citation=_CITATION,
-            language_pair=(l1, l2),
-            version=datasets.Version("1.0.0"),
-        )
-        for l1, l2 in _LANGUAGE_PAIRS
-    ]
-
-    @property
-    def manual_download_instructions(self):
-        if self.config.language_pair[1] in ["cs", "hi", "ru"]:
-            return "Please download the data manually as explained. TODO(PVP)"
-
-    @property
-    def _subsets(self):
-        return {
-            datasets.Split.TRAIN: [
-                "europarl_v9",
-                "europarl_v7_frde",
-                "paracrawl_v3",
-                "paracrawl_v1_ru",
-                "paracrawl_v3_frde",
-                "commoncrawl",
-                "commoncrawl_frde",
-                "newscommentary_v14",
-                "newscommentary_v14_frde",
-                "czeng_17",
-                "yandexcorpus",
-                "wikititles_v1",
-                "uncorpus_v1",
-                "rapid_2016_ltfi",
-                "rapid_2019",
-            ]
-            + CWMT_SUBSET_NAMES,
-            datasets.Split.VALIDATION: ["euelections_dev2019", "newsdev2019", "newstest2018"],
-        }

wmt_utils.py

@@ -1,1025 +0,0 @@
-# coding=utf-8
-# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
-#
-# 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.
-
-# Lint as: python3
-"""WMT: Translate dataset."""
-
-
-import codecs
-import functools
-import glob
-import gzip
-import itertools
-import os
-import re
-import xml.etree.cElementTree as ElementTree
-
-import datasets
-
-
-logger = datasets.logging.get_logger(__name__)
-
-
-_DESCRIPTION = """\
-Translation dataset based on the data from statmt.org.
-
-Versions exist for different years using a combination of data
-sources. The base `wmt` allows you to create a custom dataset by choosing
-your own data/language pair. This can be done as follows:
-
-```python
-from datasets import inspect_dataset, load_dataset_builder
-
-inspect_dataset("wmt19", "path/to/scripts")
-builder = load_dataset_builder(
-    "path/to/scripts/wmt_utils.py",
-    language_pair=("fr", "de"),
-    subsets={
-        datasets.Split.TRAIN: ["commoncrawl_frde"],
-        datasets.Split.VALIDATION: ["euelections_dev2019"],
-    },
-)
-
-# Standard version
-builder.download_and_prepare()
-ds = builder.as_dataset()
-
-# Streamable version
-ds = builder.as_streaming_dataset()
-```
-
-"""
-
-
-CWMT_SUBSET_NAMES = ["casia2015", "casict2011", "casict2015", "datum2015", "datum2017", "neu2017"]
-
-
-class SubDataset:
-    """Class to keep track of information on a sub-dataset of WMT."""
-
-    def __init__(self, name, target, sources, url, path, manual_dl_files=None):
-        """Sub-dataset of WMT.
-
-        Args:
-          name: `string`, a unique dataset identifier.
-          target: `string`, the target language code.
-          sources: `set<string>`, the set of source language codes.
-          url: `string` or `(string, string)`, URL(s) or URL template(s) specifying
-            where to download the raw data from. If two strings are provided, the
-            first is used for the source language and the second for the target.
-            Template strings can either contain '{src}' placeholders that will be
-            filled in with the source language code, '{0}' and '{1}' placeholders
-            that will be filled in with the source and target language codes in
-            alphabetical order, or all 3.
-          path: `string` or `(string, string)`, path(s) or path template(s)
-            specifing the path to the raw data relative to the root of the
-            downloaded archive. If two strings are provided, the dataset is assumed
-            to be made up of parallel text files, the first being the source and the
-            second the target. If one string is provided, both languages are assumed
-            to be stored within the same file and the extension is used to determine
-            how to parse it. Template strings should be formatted the same as in
-            `url`.
-          manual_dl_files: `<list>(string)` (optional), the list of files that must
-            be manually downloaded to the data directory.
-        """
-        self._paths = (path,) if isinstance(path, str) else path
-        self._urls = (url,) if isinstance(url, str) else url
-        self._manual_dl_files = manual_dl_files if manual_dl_files else []
-        self.name = name
-        self.target = target
-        self.sources = set(sources)
-
-    def _inject_language(self, src, strings):
-        """Injects languages into (potentially) template strings."""
-        if src not in self.sources:
-            raise ValueError(f"Invalid source for '{self.name}': {src}")
-
-        def _format_string(s):
-            if "{0}" in s and "{1}" and "{src}" in s:
-                return s.format(*sorted([src, self.target]), src=src)
-            elif "{0}" in s and "{1}" in s:
-                return s.format(*sorted([src, self.target]))
-            elif "{src}" in s:
-                return s.format(src=src)
-            else:
-                return s
-
-        return [_format_string(s) for s in strings]
-
-    def get_url(self, src):
-        return self._inject_language(src, self._urls)
-
-    def get_manual_dl_files(self, src):
-        return self._inject_language(src, self._manual_dl_files)
-
-    def get_path(self, src):
-        return self._inject_language(src, self._paths)
-
-
-# Subsets used in the training sets for various years of WMT.
-_TRAIN_SUBSETS = [
-    # pylint:disable=line-too-long
-    SubDataset(
-        name="commoncrawl",
-        target="en",  # fr-de pair in commoncrawl_frde
-        sources={"cs", "de", "es", "fr", "ru"},
-        url="https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-commoncrawl.zip",
-        path=("commoncrawl.{src}-en.{src}", "commoncrawl.{src}-en.en"),
-    ),
-    SubDataset(
-        name="commoncrawl_frde",
-        target="de",
-        sources={"fr"},
-        url=(
-            "https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/fr-de/bitexts/commoncrawl.fr.gz",
-            "https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/fr-de/bitexts/commoncrawl.de.gz",
-        ),
-        path=("", ""),
-    ),
-    SubDataset(
-        name="czeng_10",
-        target="en",
-        sources={"cs"},
-        url="http://ufal.mff.cuni.cz/czeng/czeng10",
-        manual_dl_files=["data-plaintext-format.%d.tar" % i for i in range(10)],
-        # Each tar contains multiple files, which we process specially in
-        # _parse_czeng.
-        path=("data.plaintext-format/??train.gz",) * 10,
-    ),
-    SubDataset(
-        name="czeng_16pre",
-        target="en",
-        sources={"cs"},
-        url="http://ufal.mff.cuni.cz/czeng/czeng16pre",
-        manual_dl_files=["czeng16pre.deduped-ignoring-sections.txt.gz"],
-        path="",
-    ),
-    SubDataset(
-        name="czeng_16",
-        target="en",
-        sources={"cs"},
-        url="http://ufal.mff.cuni.cz/czeng",
-        manual_dl_files=["data-plaintext-format.%d.tar" % i for i in range(10)],
-        # Each tar contains multiple files, which we process specially in
-        # _parse_czeng.
-        path=("data.plaintext-format/??train.gz",) * 10,
-    ),
-    SubDataset(
-        # This dataset differs from the above in the filtering that is applied
-        # during parsing.
-        name="czeng_17",
-        target="en",
-        sources={"cs"},
-        url="http://ufal.mff.cuni.cz/czeng",
-        manual_dl_files=["data-plaintext-format.%d.tar" % i for i in range(10)],
-        # Each tar contains multiple files, which we process specially in
-        # _parse_czeng.
-        path=("data.plaintext-format/??train.gz",) * 10,
-    ),
-    SubDataset(
-        name="dcep_v1",
-        target="en",
-        sources={"lv"},
-        url="https://huggingface.co/datasets/wmt/wmt17/resolve/main-zip/translation-task/dcep.lv-en.v1.zip",
-        path=("dcep.en-lv/dcep.lv", "dcep.en-lv/dcep.en"),
-    ),
-    SubDataset(
-        name="europarl_v7",
-        target="en",
-        sources={"cs", "de", "es", "fr"},
-        url="https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-europarl-v7.zip",
-        path=("training/europarl-v7.{src}-en.{src}", "training/europarl-v7.{src}-en.en"),
-    ),
-    SubDataset(
-        name="europarl_v7_frde",
-        target="de",
-        sources={"fr"},
-        url=(
-            "https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/fr-de/bitexts/europarl-v7.fr.gz",
-            "https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/fr-de/bitexts/europarl-v7.de.gz",
-        ),
-        path=("", ""),
-    ),
-    SubDataset(
-        name="europarl_v8_18",
-        target="en",
-        sources={"et", "fi"},
-        url="https://huggingface.co/datasets/wmt/wmt18/resolve/main-zip/translation-task/training-parallel-ep-v8.zip",
-        path=("training/europarl-v8.{src}-en.{src}", "training/europarl-v8.{src}-en.en"),
-    ),
-    SubDataset(
-        name="europarl_v8_16",
-        target="en",
-        sources={"fi", "ro"},
-        url="https://huggingface.co/datasets/wmt/wmt16/resolve/main-zip/translation-task/training-parallel-ep-v8.zip",
-        path=("training-parallel-ep-v8/europarl-v8.{src}-en.{src}", "training-parallel-ep-v8/europarl-v8.{src}-en.en"),
-    ),
-    SubDataset(
-        name="europarl_v9",
-        target="en",
-        sources={"cs", "de", "fi", "lt"},
-        url="https://huggingface.co/datasets/wmt/europarl/resolve/main/v9/training/europarl-v9.{src}-en.tsv.gz",
-        path="",
-    ),
-    SubDataset(
-        name="gigafren",
-        target="en",
-        sources={"fr"},
-        url="https://huggingface.co/datasets/wmt/wmt10/resolve/main-zip/training-giga-fren.zip",
-        path=("giga-fren.release2.fixed.fr.gz", "giga-fren.release2.fixed.en.gz"),
-    ),
-    SubDataset(
-        name="hindencorp_01",
-        target="en",
-        sources={"hi"},
-        url="http://ufallab.ms.mff.cuni.cz/~bojar/hindencorp",
-        manual_dl_files=["hindencorp0.1.gz"],
-        path="",
-    ),
-    SubDataset(
-        name="leta_v1",
-        target="en",
-        sources={"lv"},
-        url="https://huggingface.co/datasets/wmt/wmt17/resolve/main-zip/translation-task/leta.v1.zip",
-        path=("LETA-lv-en/leta.lv", "LETA-lv-en/leta.en"),
-    ),
-    SubDataset(
-        name="multiun",
-        target="en",
-        sources={"es", "fr"},
-        url="https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-un.zip",
-        path=("un/undoc.2000.{src}-en.{src}", "un/undoc.2000.{src}-en.en"),
-    ),
-    SubDataset(
-        name="newscommentary_v9",
-        target="en",
-        sources={"cs", "de", "fr", "ru"},
-        url="https://huggingface.co/datasets/wmt/wmt14/resolve/main-zip/training-parallel-nc-v9.zip",
-        path=("training/news-commentary-v9.{src}-en.{src}", "training/news-commentary-v9.{src}-en.en"),
-    ),
-    SubDataset(
-        name="newscommentary_v10",
-        target="en",
-        sources={"cs", "de", "fr", "ru"},
-        url="https://huggingface.co/datasets/wmt/wmt15/resolve/main-zip/training-parallel-nc-v10.zip",
-        path=("news-commentary-v10.{src}-en.{src}", "news-commentary-v10.{src}-en.en"),
-    ),
-    SubDataset(
-        name="newscommentary_v11",
-        target="en",
-        sources={"cs", "de", "ru"},
-        url="https://huggingface.co/datasets/wmt/wmt16/resolve/main-zip/translation-task/training-parallel-nc-v11.zip",
-        path=(
-            "training-parallel-nc-v11/news-commentary-v11.{src}-en.{src}",
-            "training-parallel-nc-v11/news-commentary-v11.{src}-en.en",
-        ),
-    ),
-    SubDataset(
-        name="newscommentary_v12",
-        target="en",
-        sources={"cs", "de", "ru", "zh"},
-        url="https://huggingface.co/datasets/wmt/wmt17/resolve/main-zip/translation-task/training-parallel-nc-v12.zip",
-        path=("training/news-commentary-v12.{src}-en.{src}", "training/news-commentary-v12.{src}-en.en"),
-    ),
-    SubDataset(
-        name="newscommentary_v13",
-        target="en",
-        sources={"cs", "de", "ru", "zh"},
-        url="https://huggingface.co/datasets/wmt/wmt18/resolve/main-zip/translation-task/training-parallel-nc-v13.zip",
-        path=(
-            "training-parallel-nc-v13/news-commentary-v13.{src}-en.{src}",
-            "training-parallel-nc-v13/news-commentary-v13.{src}-en.en",
-        ),
-    ),
-    SubDataset(
-        name="newscommentary_v14",
-        target="en",  # fr-de pair in newscommentary_v14_frde
-        sources={"cs", "de", "kk", "ru", "zh"},
-        url="http://data.statmt.org/news-commentary/v14/training/news-commentary-v14.{0}-{1}.tsv.gz",
-        path="",
-    ),
-    SubDataset(
-        name="newscommentary_v14_frde",
-        target="de",
-        sources={"fr"},
-        url="http://data.statmt.org/news-commentary/v14/training/news-commentary-v14.de-fr.tsv.gz",
-        path="",
-    ),
-    SubDataset(
-        name="onlinebooks_v1",
-        target="en",
-        sources={"lv"},
-        url="https://huggingface.co/datasets/wmt/wmt17/resolve/main-zip/translation-task/books.lv-en.v1.zip",
-        path=("farewell/farewell.lv", "farewell/farewell.en"),
-    ),
-    SubDataset(
-        name="paracrawl_v1",
-        target="en",
-        sources={"cs", "de", "et", "fi", "ru"},
-        url="https://s3.amazonaws.com/web-language-models/paracrawl/release1/paracrawl-release1.en-{src}.zipporah0-dedup-clean.tgz",  # TODO(QL): use gzip for streaming
-        path=(
-            "paracrawl-release1.en-{src}.zipporah0-dedup-clean.{src}",
-            "paracrawl-release1.en-{src}.zipporah0-dedup-clean.en",
-        ),
-    ),
-    SubDataset(
-        name="paracrawl_v1_ru",
-        target="en",
-        sources={"ru"},
-        url="https://s3.amazonaws.com/web-language-models/paracrawl/release1/paracrawl-release1.en-ru.zipporah0-dedup-clean.tgz",  # TODO(QL): use gzip for streaming
-        path=(
-            "paracrawl-release1.en-ru.zipporah0-dedup-clean.ru",
-            "paracrawl-release1.en-ru.zipporah0-dedup-clean.en",
-        ),
-    ),
-    SubDataset(
-        name="paracrawl_v3",
-        target="en",  # fr-de pair in paracrawl_v3_frde
-        sources={"cs", "de", "fi", "lt"},
-        url="https://s3.amazonaws.com/web-language-models/paracrawl/release3/en-{src}.bicleaner07.tmx.gz",
-        path="",
-    ),
-    SubDataset(
-        name="paracrawl_v3_frde",
-        target="de",
-        sources={"fr"},
-        url=(
-            "https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/fr-de/bitexts/de-fr.bicleaner07.de.gz",
-            "https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/fr-de/bitexts/de-fr.bicleaner07.fr.gz",
-        ),
-        path=("", ""),
-    ),
-    SubDataset(
-        name="rapid_2016",
-        target="en",
-        sources={"de", "et", "fi"},
-        url="https://huggingface.co/datasets/wmt/wmt18/resolve/main-zip/translation-task/rapid2016.zip",
-        path=("rapid2016.{0}-{1}.{src}", "rapid2016.{0}-{1}.en"),
-    ),
-    SubDataset(
-        name="rapid_2016_ltfi",
-        target="en",
-        sources={"fi", "lt"},
-        url="https://tilde-model.s3-eu-west-1.amazonaws.com/rapid2016.en-{src}.tmx.zip",
-        path="rapid2016.en-{src}.tmx",
-    ),
-    SubDataset(
-        name="rapid_2019",
-        target="en",
-        sources={"de"},
-        url="https://s3-eu-west-1.amazonaws.com/tilde-model/rapid2019.de-en.zip",
-        path=("rapid2019.de-en.de", "rapid2019.de-en.en"),
-    ),
-    SubDataset(
-        name="setimes_2",
-        target="en",
-        sources={"ro", "tr"},
-        url="https://opus.nlpl.eu/download.php?f=SETIMES/v2/tmx/en-{src}.tmx.gz",
-        path="",
-    ),
-    SubDataset(
-        name="uncorpus_v1",
-        target="en",
-        sources={"ru", "zh"},
-        url="https://huggingface.co/datasets/wmt/uncorpus/resolve/main-zip/UNv1.0.en-{src}.zip",
-        path=("en-{src}/UNv1.0.en-{src}.{src}", "en-{src}/UNv1.0.en-{src}.en"),
-    ),
-    SubDataset(
-        name="wikiheadlines_fi",
-        target="en",
-        sources={"fi"},
-        url="https://huggingface.co/datasets/wmt/wmt15/resolve/main-zip/wiki-titles.zip",
-        path="wiki/fi-en/titles.fi-en",
-    ),
-    SubDataset(
-        name="wikiheadlines_hi",
-        target="en",
-        sources={"hi"},
-        url="https://huggingface.co/datasets/wmt/wmt14/resolve/main-zip/wiki-titles.zip",
-        path="wiki/hi-en/wiki-titles.hi-en",
-    ),
-    SubDataset(
-        # Verified that wmt14 and wmt15 files are identical.
-        name="wikiheadlines_ru",
-        target="en",
-        sources={"ru"},
-        url="https://huggingface.co/datasets/wmt/wmt15/resolve/main-zip/wiki-titles.zip",
-        path="wiki/ru-en/wiki.ru-en",
-    ),
-    SubDataset(
-        name="wikititles_v1",
-        target="en",
-        sources={"cs", "de", "fi", "gu", "kk", "lt", "ru", "zh"},
-        url="https://huggingface.co/datasets/wmt/wikititles/resolve/main/v1/wikititles-v1.{src}-en.tsv.gz",
-        path="",
-    ),
-    SubDataset(
-        name="yandexcorpus",
-        target="en",
-        sources={"ru"},
-        url="https://translate.yandex.ru/corpus?lang=en",
-        manual_dl_files=["1mcorpus.zip"],
-        path=("corpus.en_ru.1m.ru", "corpus.en_ru.1m.en"),
-    ),
-    # pylint:enable=line-too-long
-] + [
-    SubDataset(  # pylint:disable=g-complex-comprehension
-        name=ss,
-        target="en",
-        sources={"zh"},
-        url="https://huggingface.co/datasets/wmt/wmt18/resolve/main/cwmt-wmt/%s.zip" % ss,
-        path=("%s/*_c[hn].txt" % ss, "%s/*_en.txt" % ss),
-    )
-    for ss in CWMT_SUBSET_NAMES
-]
-
-_DEV_SUBSETS = [
-    SubDataset(
-        name="euelections_dev2019",
-        target="de",
-        sources={"fr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/euelections_dev2019.fr-de.src.fr", "dev/euelections_dev2019.fr-de.tgt.de"),
-    ),
-    SubDataset(
-        name="newsdev2014",
-        target="en",
-        sources={"hi"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newsdev2014.hi", "dev/newsdev2014.en"),
-    ),
-    SubDataset(
-        name="newsdev2015",
-        target="en",
-        sources={"fi"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newsdev2015-fien-src.{src}.sgm", "dev/newsdev2015-fien-ref.en.sgm"),
-    ),
-    SubDataset(
-        name="newsdiscussdev2015",
-        target="en",
-        sources={"ro", "tr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newsdiscussdev2015-{src}en-src.{src}.sgm", "dev/newsdiscussdev2015-{src}en-ref.en.sgm"),
-    ),
-    SubDataset(
-        name="newsdev2016",
-        target="en",
-        sources={"ro", "tr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newsdev2016-{src}en-src.{src}.sgm", "dev/newsdev2016-{src}en-ref.en.sgm"),
-    ),
-    SubDataset(
-        name="newsdev2017",
-        target="en",
-        sources={"lv", "zh"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newsdev2017-{src}en-src.{src}.sgm", "dev/newsdev2017-{src}en-ref.en.sgm"),
-    ),
-    SubDataset(
-        name="newsdev2018",
-        target="en",
-        sources={"et"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newsdev2018-{src}en-src.{src}.sgm", "dev/newsdev2018-{src}en-ref.en.sgm"),
-    ),
-    SubDataset(
-        name="newsdev2019",
-        target="en",
-        sources={"gu", "kk", "lt"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newsdev2019-{src}en-src.{src}.sgm", "dev/newsdev2019-{src}en-ref.en.sgm"),
-    ),
-    SubDataset(
-        name="newsdiscussdev2015",
-        target="en",
-        sources={"fr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newsdiscussdev2015-{src}en-src.{src}.sgm", "dev/newsdiscussdev2015-{src}en-ref.en.sgm"),
-    ),
-    SubDataset(
-        name="newsdiscusstest2015",
-        target="en",
-        sources={"fr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newsdiscusstest2015-{src}en-src.{src}.sgm", "dev/newsdiscusstest2015-{src}en-ref.en.sgm"),
-    ),
-    SubDataset(
-        name="newssyscomb2009",
-        target="en",
-        sources={"cs", "de", "es", "fr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newssyscomb2009.{src}", "dev/newssyscomb2009.en"),
-    ),
-    SubDataset(
-        name="newstest2008",
-        target="en",
-        sources={"cs", "de", "es", "fr", "hu"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/news-test2008.{src}", "dev/news-test2008.en"),
-    ),
-    SubDataset(
-        name="newstest2009",
-        target="en",
-        sources={"cs", "de", "es", "fr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newstest2009.{src}", "dev/newstest2009.en"),
-    ),
-    SubDataset(
-        name="newstest2010",
-        target="en",
-        sources={"cs", "de", "es", "fr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newstest2010.{src}", "dev/newstest2010.en"),
-    ),
-    SubDataset(
-        name="newstest2011",
-        target="en",
-        sources={"cs", "de", "es", "fr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newstest2011.{src}", "dev/newstest2011.en"),
-    ),
-    SubDataset(
-        name="newstest2012",
-        target="en",
-        sources={"cs", "de", "es", "fr", "ru"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newstest2012.{src}", "dev/newstest2012.en"),
-    ),
-    SubDataset(
-        name="newstest2013",
-        target="en",
-        sources={"cs", "de", "es", "fr", "ru"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newstest2013.{src}", "dev/newstest2013.en"),
-    ),
-    SubDataset(
-        name="newstest2014",
-        target="en",
-        sources={"cs", "de", "es", "fr", "hi", "ru"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newstest2014-{src}en-src.{src}.sgm", "dev/newstest2014-{src}en-ref.en.sgm"),
-    ),
-    SubDataset(
-        name="newstest2015",
-        target="en",
-        sources={"cs", "de", "fi", "ru"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newstest2015-{src}en-src.{src}.sgm", "dev/newstest2015-{src}en-ref.en.sgm"),
-    ),
-    SubDataset(
-        name="newsdiscusstest2015",
-        target="en",
-        sources={"fr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newsdiscusstest2015-{src}en-src.{src}.sgm", "dev/newsdiscusstest2015-{src}en-ref.en.sgm"),
-    ),
-    SubDataset(
-        name="newstest2016",
-        target="en",
-        sources={"cs", "de", "fi", "ro", "ru", "tr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newstest2016-{src}en-src.{src}.sgm", "dev/newstest2016-{src}en-ref.en.sgm"),
-    ),
-    SubDataset(
-        name="newstestB2016",
-        target="en",
-        sources={"fi"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newstestB2016-enfi-ref.{src}.sgm", "dev/newstestB2016-enfi-src.en.sgm"),
-    ),
-    SubDataset(
-        name="newstest2017",
-        target="en",
-        sources={"cs", "de", "fi", "lv", "ru", "tr", "zh"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newstest2017-{src}en-src.{src}.sgm", "dev/newstest2017-{src}en-ref.en.sgm"),
-    ),
-    SubDataset(
-        name="newstestB2017",
-        target="en",
-        sources={"fi"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newstestB2017-fien-src.fi.sgm", "dev/newstestB2017-fien-ref.en.sgm"),
-    ),
-    SubDataset(
-        name="newstest2018",
-        target="en",
-        sources={"cs", "de", "et", "fi", "ru", "tr", "zh"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
-        path=("dev/newstest2018-{src}en-src.{src}.sgm", "dev/newstest2018-{src}en-ref.en.sgm"),
-    ),
-]
-
-DATASET_MAP = {dataset.name: dataset for dataset in _TRAIN_SUBSETS + _DEV_SUBSETS}
-
-_CZENG17_FILTER = SubDataset(
-    name="czeng17_filter",
-    target="en",
-    sources={"cs"},
-    url="http://ufal.mff.cuni.cz/czeng/download.php?f=convert_czeng16_to_17.pl.zip",
-    path="convert_czeng16_to_17.pl",
-)
-
-
-class WmtConfig(datasets.BuilderConfig):
-    """BuilderConfig for WMT."""
-
-    def __init__(self, url=None, citation=None, description=None, language_pair=(None, None), subsets=None, **kwargs):
-        """BuilderConfig for WMT.
-
-        Args:
-          url: The reference URL for the dataset.
-          citation: The paper citation for the dataset.
-          description: The description of the dataset.
-          language_pair: pair of languages that will be used for translation. Should
-                     contain 2 letter coded strings. For example: ("en", "de").
-            configuration for the `datasets.features.text.TextEncoder` used for the
-            `datasets.features.text.Translation` features.
-          subsets: Dict[split, list[str]]. List of the subset to use for each of the
-            split. Note that WMT subclasses overwrite this parameter.
-          **kwargs: keyword arguments forwarded to super.
-        """
-        name = "%s-%s" % (language_pair[0], language_pair[1])
-        if "name" in kwargs:  # Add name suffix for custom configs
-            name += "." + kwargs.pop("name")
-
-        super(WmtConfig, self).__init__(name=name, description=description, **kwargs)
-
-        self.url = url or "http://www.statmt.org"
-        self.citation = citation
-        self.language_pair = language_pair
-        self.subsets = subsets
-
-        # TODO(PVP): remove when manual dir works
-        # +++++++++++++++++++++
-        if language_pair[1] in ["cs", "hi", "ru"]:
-            assert NotImplementedError(f"The dataset for {language_pair[1]}-en is currently not fully supported.")
-        # +++++++++++++++++++++
-
-
-class Wmt(datasets.GeneratorBasedBuilder):
-    """WMT translation dataset."""
-
-    BUILDER_CONFIG_CLASS = WmtConfig
-
-    def __init__(self, *args, **kwargs):
-        super(Wmt, self).__init__(*args, **kwargs)
-
-    @property
-    def _subsets(self):
-        """Subsets that make up each split of the dataset."""
-        raise NotImplementedError("This is a abstract method")
-
-    @property
-    def subsets(self):
-        """Subsets that make up each split of the dataset for the language pair."""
-        source, target = self.config.language_pair
-        filtered_subsets = {}
-        subsets = self._subsets if self.config.subsets is None else self.config.subsets
-        for split, ss_names in subsets.items():
-            filtered_subsets[split] = []
-            for ss_name in ss_names:
-                dataset = DATASET_MAP[ss_name]
-                if dataset.target != target or source not in dataset.sources:
-                    logger.info("Skipping sub-dataset that does not include language pair: %s", ss_name)
-                else:
-                    filtered_subsets[split].append(ss_name)
-        logger.info("Using sub-datasets: %s", filtered_subsets)
-        return filtered_subsets
-
-    def _info(self):
-        src, target = self.config.language_pair
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {"translation": datasets.features.Translation(languages=self.config.language_pair)}
-            ),
-            supervised_keys=(src, target),
-            homepage=self.config.url,
-            citation=self.config.citation,
-        )
-
-    def _vocab_text_gen(self, split_subsets, extraction_map, language):
-        for _, ex in self._generate_examples(split_subsets, extraction_map, with_translation=False):
-            yield ex[language]
-
-    def _split_generators(self, dl_manager):
-        source, _ = self.config.language_pair
-        manual_paths_dict = {}
-        urls_to_download = {}
-        for ss_name in itertools.chain.from_iterable(self.subsets.values()):
-            if ss_name == "czeng_17":
-                # CzEng1.7 is CzEng1.6 with some blocks filtered out. We must download
-                # the filtering script so we can parse out which blocks need to be
-                # removed.
-                urls_to_download[_CZENG17_FILTER.name] = _CZENG17_FILTER.get_url(source)
-
-            # get dataset
-            dataset = DATASET_MAP[ss_name]
-            if dataset.get_manual_dl_files(source):
-                # TODO(PVP): following two lines skip configs that are incomplete for now
-                # +++++++++++++++++++++
-                logger.info("Skipping {dataset.name} for now. Incomplete dataset for {self.config.name}")
-                continue
-                # +++++++++++++++++++++
-
-                manual_dl_files = dataset.get_manual_dl_files(source)
-                manual_paths = [
-                    os.path.join(os.path.abspath(os.path.expanduser(dl_manager.manual_dir)), fname)
-                    for fname in manual_dl_files
-                ]
-                assert all(
-                    os.path.exists(path) for path in manual_paths
-                ), 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)}"
-
-                # set manual path for correct subset
-                manual_paths_dict[ss_name] = manual_paths
-            else:
-                urls_to_download[ss_name] = dataset.get_url(source)
-
-        # Download and extract files from URLs.
-        downloaded_files = dl_manager.download_and_extract(urls_to_download)
-        # Extract manually downloaded files.
-        manual_files = dl_manager.extract(manual_paths_dict)
-        extraction_map = dict(downloaded_files, **manual_files)
-
-        for language in self.config.language_pair:
-            self._vocab_text_gen(self.subsets[datasets.Split.TRAIN], extraction_map, language)
-
-        return [
-            datasets.SplitGenerator(  # pylint:disable=g-complex-comprehension
-                name=split, gen_kwargs={"split_subsets": split_subsets, "extraction_map": extraction_map}
-            )
-            for split, split_subsets in self.subsets.items()
-        ]
-
-    def _generate_examples(self, split_subsets, extraction_map, with_translation=True):
-        """Returns the examples in the raw (text) form."""
-        source, _ = self.config.language_pair
-
-        def _get_local_paths(dataset, extract_dirs):
-            rel_paths = dataset.get_path(source)
-            if len(extract_dirs) == 1:
-                extract_dirs = extract_dirs * len(rel_paths)
-            return [
-                os.path.join(ex_dir, rel_path) if rel_path else ex_dir
-                for ex_dir, rel_path in zip(extract_dirs, rel_paths)
-            ]
-
-        def _get_filenames(dataset):
-            rel_paths = dataset.get_path(source)
-            urls = dataset.get_url(source)
-            if len(urls) == 1:
-                urls = urls * len(rel_paths)
-            return [rel_path if rel_path else os.path.basename(url) for url, rel_path in zip(urls, rel_paths)]
-
-        for ss_name in split_subsets:
-            # TODO(PVP) remove following five lines when manual data works
-            # +++++++++++++++++++++
-            dataset = DATASET_MAP[ss_name]
-            source, _ = self.config.language_pair
-            if dataset.get_manual_dl_files(source):
-                logger.info(f"Skipping {dataset.name} for now. Incomplete dataset for {self.config.name}")
-                continue
-            # +++++++++++++++++++++
-
-            logger.info("Generating examples from: %s", ss_name)
-            dataset = DATASET_MAP[ss_name]
-            extract_dirs = extraction_map[ss_name]
-            files = _get_local_paths(dataset, extract_dirs)
-            filenames = _get_filenames(dataset)
-
-            sub_generator_args = tuple(files)
-
-            if ss_name.startswith("czeng"):
-                if ss_name.endswith("16pre"):
-                    sub_generator = functools.partial(_parse_tsv, language_pair=("en", "cs"))
-                    sub_generator_args += tuple(filenames)
-                elif ss_name.endswith("17"):
-                    filter_path = _get_local_paths(_CZENG17_FILTER, extraction_map[_CZENG17_FILTER.name])[0]
-                    sub_generator = functools.partial(_parse_czeng, filter_path=filter_path)
-                else:
-                    sub_generator = _parse_czeng
-            elif ss_name == "hindencorp_01":
-                sub_generator = _parse_hindencorp
-            elif len(files) == 2:
-                if ss_name.endswith("_frde"):
-                    sub_generator = _parse_frde_bitext
-                else:
-                    sub_generator = _parse_parallel_sentences
-                    sub_generator_args += tuple(filenames)
-            elif len(files) == 1:
-                fname = filenames[0]
-                # Note: Due to formatting used by `download_manager`, the file
-                # extension may not be at the end of the file path.
-                if ".tsv" in fname:
-                    sub_generator = _parse_tsv
-                    sub_generator_args += tuple(filenames)
-                elif (
-                    ss_name.startswith("newscommentary_v14")
-                    or ss_name.startswith("europarl_v9")
-                    or ss_name.startswith("wikititles_v1")
-                ):
-                    sub_generator = functools.partial(_parse_tsv, language_pair=self.config.language_pair)
-                    sub_generator_args += tuple(filenames)
-                elif "tmx" in fname or ss_name.startswith("paracrawl_v3"):
-                    sub_generator = _parse_tmx
-                elif ss_name.startswith("wikiheadlines"):
-                    sub_generator = _parse_wikiheadlines
-                else:
-                    raise ValueError("Unsupported file format: %s" % fname)
-            else:
-                raise ValueError("Invalid number of files: %d" % len(files))
-
-            for sub_key, ex in sub_generator(*sub_generator_args):
-                if not all(ex.values()):
-                    continue
-                # TODO(adarob): Add subset feature.
-                # ex["subset"] = subset
-                key = f"{ss_name}/{sub_key}"
-                if with_translation is True:
-                    ex = {"translation": ex}
-                yield key, ex
-
-
-def _parse_parallel_sentences(f1, f2, filename1, filename2):
-    """Returns examples from parallel SGML or text files, which may be gzipped."""
-
-    def _parse_text(path, original_filename):
-        """Returns the sentences from a single text file, which may be gzipped."""
-        split_path = original_filename.split(".")
-
-        if split_path[-1] == "gz":
-            lang = split_path[-2]
-
-            def gen():
-                with open(path, "rb") as f, gzip.GzipFile(fileobj=f) as g:
-                    for line in g:
-                        yield line.decode("utf-8").rstrip()
-
-            return gen(), lang
-
-        if split_path[-1] == "txt":
-            # CWMT
-            lang = split_path[-2].split("_")[-1]
-            lang = "zh" if lang in ("ch", "cn", "c[hn]") else lang
-        else:
-            lang = split_path[-1]
-
-        def gen():
-            with open(path, "rb") as f:
-                for line in f:
-                    yield line.decode("utf-8").rstrip()
-
-        return gen(), lang
-
-    def _parse_sgm(path, original_filename):
-        """Returns sentences from a single SGML file."""
-        lang = original_filename.split(".")[-2]
-        # Note: We can't use the XML parser since some of the files are badly
-        # formatted.
-        seg_re = re.compile(r"<seg id=\"\d+\">(.*)</seg>")
-
-        def gen():
-            with open(path, encoding="utf-8") as f:
-                for line in f:
-                    seg_match = re.match(seg_re, line)
-                    if seg_match:
-                        assert len(seg_match.groups()) == 1
-                        yield seg_match.groups()[0]
-
-        return gen(), lang
-
-    parse_file = _parse_sgm if os.path.basename(f1).endswith(".sgm") else _parse_text
-
-    # Some datasets (e.g., CWMT) contain multiple parallel files specified with
-    # a wildcard. We sort both sets to align them and parse them one by one.
-    f1_files = sorted(glob.glob(f1))
-    f2_files = sorted(glob.glob(f2))
-
-    assert f1_files and f2_files, "No matching files found: %s, %s." % (f1, f2)
-    assert len(f1_files) == len(f2_files), "Number of files do not match: %d vs %d for %s vs %s." % (
-        len(f1_files),
-        len(f2_files),
-        f1,
-        f2,
-    )
-
-    for f_id, (f1_i, f2_i) in enumerate(zip(sorted(f1_files), sorted(f2_files))):
-        l1_sentences, l1 = parse_file(f1_i, filename1)
-        l2_sentences, l2 = parse_file(f2_i, filename2)
-
-        for line_id, (s1, s2) in enumerate(zip(l1_sentences, l2_sentences)):
-            key = f"{f_id}/{line_id}"
-            yield key, {l1: s1, l2: s2}
-
-
-def _parse_frde_bitext(fr_path, de_path):
-    with open(fr_path, encoding="utf-8") as fr_f:
-        with open(de_path, encoding="utf-8") as de_f:
-            for line_id, (s1, s2) in enumerate(zip(fr_f, de_f)):
-                yield line_id, {"fr": s1.rstrip(), "de": s2.rstrip()}
-
-
-def _parse_tmx(path):
-    """Generates examples from TMX file."""
-
-    def _get_tuv_lang(tuv):
-        for k, v in tuv.items():
-            if k.endswith("}lang"):
-                return v
-        raise AssertionError("Language not found in `tuv` attributes.")
-
-    def _get_tuv_seg(tuv):
-        segs = tuv.findall("seg")
-        assert len(segs) == 1, "Invalid number of segments: %d" % len(segs)
-        return segs[0].text
-
-    with open(path, "rb") as f:
-        # Workaround due to: https://github.com/tensorflow/tensorflow/issues/33563
-        utf_f = codecs.getreader("utf-8")(f)
-        for line_id, (_, elem) in enumerate(ElementTree.iterparse(utf_f)):
-            if elem.tag == "tu":
-                yield line_id, {_get_tuv_lang(tuv): _get_tuv_seg(tuv) for tuv in elem.iterfind("tuv")}
-                elem.clear()
-
-
-def _parse_tsv(path, filename, language_pair=None):
-    """Generates examples from TSV file."""
-    if language_pair is None:
-        lang_match = re.match(r".*\.([a-z][a-z])-([a-z][a-z])\.tsv", filename)
-        assert lang_match is not None, "Invalid TSV filename: %s" % filename
-        l1, l2 = lang_match.groups()
-    else:
-        l1, l2 = language_pair
-    with open(path, encoding="utf-8") as f:
-        for j, line in enumerate(f):
-            cols = line.split("\t")
-            if len(cols) != 2:
-                logger.warning("Skipping line %d in TSV (%s) with %d != 2 columns.", j, path, len(cols))
-                continue
-            s1, s2 = cols
-            yield j, {l1: s1.strip(), l2: s2.strip()}
-
-
-def _parse_wikiheadlines(path):
-    """Generates examples from Wikiheadlines dataset file."""
-    lang_match = re.match(r".*\.([a-z][a-z])-([a-z][a-z])$", path)
-    assert lang_match is not None, "Invalid Wikiheadlines filename: %s" % path
-    l1, l2 = lang_match.groups()
-    with open(path, encoding="utf-8") as f:
-        for line_id, line in enumerate(f):
-            s1, s2 = line.split("|||")
-            yield line_id, {l1: s1.strip(), l2: s2.strip()}
-
-
-def _parse_czeng(*paths, **kwargs):
-    """Generates examples from CzEng v1.6, with optional filtering for v1.7."""
-    filter_path = kwargs.get("filter_path", None)
-    if filter_path:
-        re_block = re.compile(r"^[^-]+-b(\d+)-\d\d[tde]")
-        with open(filter_path, encoding="utf-8") as f:
-            bad_blocks = {blk for blk in re.search(r"qw{([\s\d]*)}", f.read()).groups()[0].split()}
-        logger.info("Loaded %d bad blocks to filter from CzEng v1.6 to make v1.7.", len(bad_blocks))
-
-    for path in paths:
-        for gz_path in sorted(glob.glob(path)):
-            with open(gz_path, "rb") as g, gzip.GzipFile(fileobj=g) as f:
-                filename = os.path.basename(gz_path)
-                for line_id, line in enumerate(f):
-                    line = line.decode("utf-8")  # required for py3
-                    if not line.strip():
-                        continue
-                    id_, unused_score, cs, en = line.split("\t")
-                    if filter_path:
-                        block_match = re.match(re_block, id_)
-                        if block_match and block_match.groups()[0] in bad_blocks:
-                            continue
-                    sub_key = f"{filename}/{line_id}"
-                    yield sub_key, {
-                        "cs": cs.strip(),
-                        "en": en.strip(),
-                    }
-
-
-def _parse_hindencorp(path):
-    with open(path, encoding="utf-8") as f:
-        for line_id, line in enumerate(f):
-            split_line = line.split("\t")
-            if len(split_line) != 5:
-                logger.warning("Skipping invalid HindEnCorp line: %s", line)
-                continue
-            yield line_id, {"translation": {"en": split_line[3].strip(), "hi": split_line[4].strip()}}