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Update files from the datasets library (from 1.16.0)

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Release notes: https://github.com/huggingface/datasets/releases/tag/1.16.0

Files changed (4) hide show
  1. README.md +7 -0
  2. dataset_infos.json +1 -1
  3. dummy/cs-en/1.0.0/dummy_data.zip +2 -2
  4. wmt_utils.py +105 -100
README.md CHANGED
@@ -1,5 +1,12 @@
1
  ---
 
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  paperswithcode_id: wmt-2014
 
 
 
 
 
 
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  ---
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  # Dataset Card for "wmt14"
 
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  ---
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+ pretty_name: WMT14
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  paperswithcode_id: wmt-2014
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+ multilinguality:
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+ - translation
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+ task_categories:
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+ - conditional-text-generation
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+ task_ids:
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+ - machine-translation
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  ---
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  # Dataset Card for "wmt14"
dataset_infos.json CHANGED
@@ -1 +1 @@
1
- {"cs-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@InProceedings{bojar-EtAl:2014:W14-33,\n author = {Bojar, Ondrej and Buck, Christian and Federmann, Christian and Haddow, Barry and Koehn, Philipp and Leveling, Johannes and Monz, Christof and Pecina, Pavel and Post, Matt and Saint-Amand, Herve and Soricut, Radu and Specia, Lucia and Tamchyna, Ale\u000b{s}},\n title = {Findings of the 2014 Workshop on Statistical Machine Translation},\n booktitle = {Proceedings of the Ninth Workshop on Statistical Machine Translation},\n month = {June},\n year = {2014},\n address = {Baltimore, Maryland, USA},\n publisher = {Association for Computational Linguistics},\n pages = {12--58},\n url = {http://www.aclweb.org/anthology/W/W14/W14-3302}\n}\n", "homepage": "http://www.statmt.org/wmt14/translation-task.html", "license": "", "features": {"translation": {"languages": ["cs", "en"], "id": null, "_type": "Translation"}}, "supervised_keys": {"input": "cs", "output": "en"}, "builder_name": "wmt14", "config_name": "cs-en", "version": {"version_str": "1.0.0", "description": null, "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 759321, "num_examples": 3003, "dataset_name": "wmt14"}, "train": {"name": "train", "num_bytes": 281479898, "num_examples": 953621, "dataset_name": "wmt14"}, "validation": {"name": "validation", "num_bytes": 703973, "num_examples": 3000, "dataset_name": "wmt14"}}, "download_checksums": {"https://huggingface.co/datasets/wmt/wmt13/resolve/main/training-parallel-europarl-v7.tgz": {"num_bytes": 657632379, "checksum": "0224c7c710c8a063dfd893b0cc0830202d61f4c75c17eb8e31836103d27d96e7"}, "https://huggingface.co/datasets/wmt/wmt13/resolve/main/training-parallel-commoncrawl.tgz": {"num_bytes": 918311367, "checksum": "c7a74e2ea01ac6c920123108627e35278d4ccb5701e15428ffa34de86fa3a9e5"}, "https://huggingface.co/datasets/wmt/wmt14/resolve/main/training-parallel-nc-v9.tgz": {"num_bytes": 80418416, "checksum": "cb8953f292298e6877ae433c98912b927cb0766b303f4540512ddd286c748485"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz": {"num_bytes": 38654961, "checksum": "7a7deccf82ebb05ba508dba5eb21356492224e8f630ec4f992132b029b4b25e7"}}, "download_size": 1695017123, "dataset_size": 282943192, "size_in_bytes": 1977960315}}
 
1
+ {"cs-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@InProceedings{bojar-EtAl:2014:W14-33,\n author = {Bojar, Ondrej and Buck, Christian and Federmann, Christian and Haddow, Barry and Koehn, Philipp and Leveling, Johannes and Monz, Christof and Pecina, Pavel and Post, Matt and Saint-Amand, Herve and Soricut, Radu and Specia, Lucia and Tamchyna, Ale\u000b{s}},\n title = {Findings of the 2014 Workshop on Statistical Machine Translation},\n booktitle = {Proceedings of the Ninth Workshop on Statistical Machine Translation},\n month = {June},\n year = {2014},\n address = {Baltimore, Maryland, USA},\n publisher = {Association for Computational Linguistics},\n pages = {12--58},\n url = {http://www.aclweb.org/anthology/W/W14/W14-3302}\n}\n", "homepage": "http://www.statmt.org/wmt14/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": "wmt14", "config_name": "cs-en", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 280992794, "num_examples": 953621, "dataset_name": "wmt14"}, "validation": {"name": "validation", "num_bytes": 702473, "num_examples": 3000, "dataset_name": "wmt14"}, "test": {"name": "test", "num_bytes": 757817, "num_examples": 3003, "dataset_name": "wmt14"}}, "download_checksums": {"https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-europarl-v7.zip": {"num_bytes": 658092427, "checksum": "5b2d8b32c2396da739b4e731871c597fcc6e75729becd74619d0712eecf7770e"}, "https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-commoncrawl.zip": {"num_bytes": 918734483, "checksum": "5ffe980072ea29adfd84568d099bea366d9f72772b988e670794ae851b4e5627"}, "https://huggingface.co/datasets/wmt/wmt14/resolve/main-zip/training-parallel-nc-v9.zip": {"num_bytes": 80462375, "checksum": "ce199f93ec56ff480137ba29f0819f9a22e70d88be6d7458f112303d67d623d5"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip": {"num_bytes": 38714274, "checksum": "d796e363740fdc4261aa6f5a3d2f8223e3adaee7d737b7724863325b8956dfd1"}}, "download_size": 1696003559, "post_processing_size": null, "dataset_size": 282453084, "size_in_bytes": 1978456643}, "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@InProceedings{bojar-EtAl:2014:W14-33,\n author = {Bojar, Ondrej and Buck, Christian and Federmann, Christian and Haddow, Barry and Koehn, Philipp and Leveling, Johannes and Monz, Christof and Pecina, Pavel and Post, Matt and Saint-Amand, Herve and Soricut, Radu and Specia, Lucia and Tamchyna, Ale\u000b{s}},\n title = {Findings of the 2014 Workshop on Statistical Machine Translation},\n booktitle = {Proceedings of the Ninth Workshop on Statistical Machine Translation},\n month = {June},\n year = {2014},\n address = {Baltimore, Maryland, USA},\n publisher = {Association for Computational Linguistics},\n pages = {12--58},\n url = {http://www.aclweb.org/anthology/W/W14/W14-3302}\n}\n", "homepage": "http://www.statmt.org/wmt14/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": "wmt14", "config_name": "de-en", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1358410408, "num_examples": 4508785, "dataset_name": "wmt14"}, "validation": {"name": "validation", "num_bytes": 736415, "num_examples": 3000, "dataset_name": "wmt14"}, "test": {"name": "test", "num_bytes": 777334, "num_examples": 3003, "dataset_name": "wmt14"}}, "download_checksums": {"https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-europarl-v7.zip": {"num_bytes": 658092427, "checksum": "5b2d8b32c2396da739b4e731871c597fcc6e75729becd74619d0712eecf7770e"}, "https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-commoncrawl.zip": {"num_bytes": 918734483, "checksum": "5ffe980072ea29adfd84568d099bea366d9f72772b988e670794ae851b4e5627"}, "https://huggingface.co/datasets/wmt/wmt14/resolve/main-zip/training-parallel-nc-v9.zip": {"num_bytes": 80462375, "checksum": "ce199f93ec56ff480137ba29f0819f9a22e70d88be6d7458f112303d67d623d5"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip": {"num_bytes": 38714274, "checksum": "d796e363740fdc4261aa6f5a3d2f8223e3adaee7d737b7724863325b8956dfd1"}}, "download_size": 1696003559, "post_processing_size": null, "dataset_size": 1359924157, "size_in_bytes": 3055927716}, "fr-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@InProceedings{bojar-EtAl:2014:W14-33,\n author = {Bojar, Ondrej and Buck, Christian and Federmann, Christian and Haddow, Barry and Koehn, Philipp and Leveling, Johannes and Monz, Christof and Pecina, Pavel and Post, Matt and Saint-Amand, Herve and Soricut, Radu and Specia, Lucia and Tamchyna, Ale\u000b{s}},\n title = {Findings of the 2014 Workshop on Statistical Machine Translation},\n booktitle = {Proceedings of the Ninth Workshop on Statistical Machine Translation},\n month = {June},\n year = {2014},\n address = {Baltimore, Maryland, USA},\n publisher = {Association for Computational Linguistics},\n pages = {12--58},\n url = {http://www.aclweb.org/anthology/W/W14/W14-3302}\n}\n", "homepage": "http://www.statmt.org/wmt14/translation-task.html", "license": "", "features": {"translation": {"languages": ["fr", "en"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": {"input": "fr", "output": "en"}, "task_templates": null, "builder_name": "wmt14", "config_name": "fr-en", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 14752554924, "num_examples": 40836715, "dataset_name": "wmt14"}, "validation": {"name": "validation", "num_bytes": 744447, "num_examples": 3000, "dataset_name": "wmt14"}, "test": {"name": "test", "num_bytes": 838857, "num_examples": 3003, "dataset_name": "wmt14"}}, "download_checksums": {"https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-europarl-v7.zip": {"num_bytes": 658092427, "checksum": "5b2d8b32c2396da739b4e731871c597fcc6e75729becd74619d0712eecf7770e"}, "https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-commoncrawl.zip": {"num_bytes": 918734483, "checksum": "5ffe980072ea29adfd84568d099bea366d9f72772b988e670794ae851b4e5627"}, "https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-un.zip": {"num_bytes": 2366237633, "checksum": "74f07002e053c81bc7f73b4fdab58e7987e831338748f264cbda82a8b062d2e2"}, "https://huggingface.co/datasets/wmt/wmt14/resolve/main-zip/training-parallel-nc-v9.zip": {"num_bytes": 80462375, "checksum": "ce199f93ec56ff480137ba29f0819f9a22e70d88be6d7458f112303d67d623d5"}, "https://huggingface.co/datasets/wmt/wmt10/resolve/main-zip/training-giga-fren.zip": {"num_bytes": 2595877717, "checksum": "9439f86523e5dff3f923526dbf6c6929da1786c18dbf64436d2b7564b83aaba3"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip": {"num_bytes": 38714274, "checksum": "d796e363740fdc4261aa6f5a3d2f8223e3adaee7d737b7724863325b8956dfd1"}}, "download_size": 6658118909, "post_processing_size": null, "dataset_size": 14754138228, "size_in_bytes": 21412257137}, "hi-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@InProceedings{bojar-EtAl:2014:W14-33,\n author = {Bojar, Ondrej and Buck, Christian and Federmann, Christian and Haddow, Barry and Koehn, Philipp and Leveling, Johannes and Monz, Christof and Pecina, Pavel and Post, Matt and Saint-Amand, Herve and Soricut, Radu and Specia, Lucia and Tamchyna, Ale\u000b{s}},\n title = {Findings of the 2014 Workshop on Statistical Machine Translation},\n booktitle = {Proceedings of the Ninth Workshop on Statistical Machine Translation},\n month = {June},\n year = {2014},\n address = {Baltimore, Maryland, USA},\n publisher = {Association for Computational Linguistics},\n pages = {12--58},\n url = {http://www.aclweb.org/anthology/W/W14/W14-3302}\n}\n", "homepage": "http://www.statmt.org/wmt14/translation-task.html", "license": "", "features": {"translation": {"languages": ["hi", "en"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": {"input": "hi", "output": "en"}, "task_templates": null, "builder_name": "wmt14", "config_name": "hi-en", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1936035, "num_examples": 32863, "dataset_name": "wmt14"}, "validation": {"name": "validation", "num_bytes": 181465, "num_examples": 520, "dataset_name": "wmt14"}, "test": {"name": "test", "num_bytes": 1075016, "num_examples": 2507, "dataset_name": "wmt14"}}, "download_checksums": {"https://huggingface.co/datasets/wmt/wmt14/resolve/main-zip/wiki-titles.zip": {"num_bytes": 8165410, "checksum": "72aa3109be74d0ecadc82c1121118878934ca234f260cfd4e4766a25e16fdbb1"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip": {"num_bytes": 38714274, "checksum": "d796e363740fdc4261aa6f5a3d2f8223e3adaee7d737b7724863325b8956dfd1"}}, "download_size": 46879684, "post_processing_size": null, "dataset_size": 3192516, "size_in_bytes": 50072200}, "ru-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@InProceedings{bojar-EtAl:2014:W14-33,\n author = {Bojar, Ondrej and Buck, Christian and Federmann, Christian and Haddow, Barry and Koehn, Philipp and Leveling, Johannes and Monz, Christof and Pecina, Pavel and Post, Matt and Saint-Amand, Herve and Soricut, Radu and Specia, Lucia and Tamchyna, Ale\u000b{s}},\n title = {Findings of the 2014 Workshop on Statistical Machine Translation},\n booktitle = {Proceedings of the Ninth Workshop on Statistical Machine Translation},\n month = {June},\n year = {2014},\n address = {Baltimore, Maryland, USA},\n publisher = {Association for Computational Linguistics},\n pages = {12--58},\n url = {http://www.aclweb.org/anthology/W/W14/W14-3302}\n}\n", "homepage": "http://www.statmt.org/wmt14/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": "wmt14", "config_name": "ru-en", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 433210270, "num_examples": 1486965, "dataset_name": "wmt14"}, "validation": {"name": "validation", "num_bytes": 977946, "num_examples": 3000, "dataset_name": "wmt14"}, "test": {"name": "test", "num_bytes": 1087746, "num_examples": 3003, "dataset_name": "wmt14"}}, "download_checksums": {"https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-commoncrawl.zip": {"num_bytes": 918734483, "checksum": "5ffe980072ea29adfd84568d099bea366d9f72772b988e670794ae851b4e5627"}, "https://huggingface.co/datasets/wmt/wmt14/resolve/main-zip/training-parallel-nc-v9.zip": {"num_bytes": 80462375, "checksum": "ce199f93ec56ff480137ba29f0819f9a22e70d88be6d7458f112303d67d623d5"}, "https://huggingface.co/datasets/wmt/wmt15/resolve/main-zip/wiki-titles.zip": {"num_bytes": 9485604, "checksum": "b3134566261b39d830eed345df1be1864039339cfeccf24b1bf86398c9e4a87c"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip": {"num_bytes": 38714274, "checksum": "d796e363740fdc4261aa6f5a3d2f8223e3adaee7d737b7724863325b8956dfd1"}}, "download_size": 1047396736, "post_processing_size": null, "dataset_size": 435275962, "size_in_bytes": 1482672698}}
dummy/cs-en/1.0.0/dummy_data.zip CHANGED
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wmt_utils.py CHANGED
@@ -96,7 +96,7 @@ class SubDataset:
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  def _inject_language(self, src, strings):
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  """Injects languages into (potentially) template strings."""
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  if src not in self.sources:
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- raise ValueError("Invalid source for '{0}': {1}".format(self.name, src))
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  def _format_string(s):
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  if "{0}" in s and "{1}" and "{src}" in s:
@@ -127,7 +127,7 @@ _TRAIN_SUBSETS = [
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  name="commoncrawl",
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  target="en", # fr-de pair in commoncrawl_frde
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  sources={"cs", "de", "es", "fr", "ru"},
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- url="https://huggingface.co/datasets/wmt/wmt13/resolve/main/training-parallel-commoncrawl.tgz",
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  path=("commoncrawl.{src}-en.{src}", "commoncrawl.{src}-en.en"),
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  ),
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  SubDataset(
@@ -184,14 +184,14 @@ _TRAIN_SUBSETS = [
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  name="dcep_v1",
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  target="en",
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  sources={"lv"},
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- url="https://huggingface.co/datasets/wmt/wmt17/resolve/main/translation-task/dcep.lv-en.v1.tgz",
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  path=("dcep.en-lv/dcep.lv", "dcep.en-lv/dcep.en"),
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  ),
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  SubDataset(
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  name="europarl_v7",
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  target="en",
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  sources={"cs", "de", "es", "fr"},
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- url="https://huggingface.co/datasets/wmt/wmt13/resolve/main/training-parallel-europarl-v7.tgz",
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  path=("training/europarl-v7.{src}-en.{src}", "training/europarl-v7.{src}-en.en"),
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  ),
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  SubDataset(
@@ -208,14 +208,14 @@ _TRAIN_SUBSETS = [
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  name="europarl_v8_18",
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  target="en",
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  sources={"et", "fi"},
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- url="https://huggingface.co/datasets/wmt/wmt18/resolve/main/translation-task/training-parallel-ep-v8.tgz",
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  path=("training/europarl-v8.{src}-en.{src}", "training/europarl-v8.{src}-en.en"),
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  ),
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  SubDataset(
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  name="europarl_v8_16",
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  target="en",
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  sources={"fi", "ro"},
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- url="https://huggingface.co/datasets/wmt/wmt16/resolve/main/translation-task/training-parallel-ep-v8.tgz",
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  path=("training-parallel-ep-v8/europarl-v8.{src}-en.{src}", "training-parallel-ep-v8/europarl-v8.{src}-en.en"),
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  ),
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  SubDataset(
@@ -229,7 +229,7 @@ _TRAIN_SUBSETS = [
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  name="gigafren",
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  target="en",
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  sources={"fr"},
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- url="https://huggingface.co/datasets/wmt/wmt10/resolve/main/training-giga-fren.tar",
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  path=("giga-fren.release2.fixed.fr.gz", "giga-fren.release2.fixed.en.gz"),
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  ),
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  SubDataset(
@@ -244,35 +244,35 @@ _TRAIN_SUBSETS = [
244
  name="leta_v1",
245
  target="en",
246
  sources={"lv"},
247
- url="https://huggingface.co/datasets/wmt/wmt17/resolve/main/translation-task/leta.v1.tgz",
248
  path=("LETA-lv-en/leta.lv", "LETA-lv-en/leta.en"),
249
  ),
250
  SubDataset(
251
  name="multiun",
252
  target="en",
253
  sources={"es", "fr"},
254
- url="https://huggingface.co/datasets/wmt/wmt13/resolve/main/training-parallel-un.tgz",
255
  path=("un/undoc.2000.{src}-en.{src}", "un/undoc.2000.{src}-en.en"),
256
  ),
257
  SubDataset(
258
  name="newscommentary_v9",
259
  target="en",
260
  sources={"cs", "de", "fr", "ru"},
261
- url="https://huggingface.co/datasets/wmt/wmt14/resolve/main/training-parallel-nc-v9.tgz",
262
  path=("training/news-commentary-v9.{src}-en.{src}", "training/news-commentary-v9.{src}-en.en"),
263
  ),
264
  SubDataset(
265
  name="newscommentary_v10",
266
  target="en",
267
  sources={"cs", "de", "fr", "ru"},
268
- url="https://huggingface.co/datasets/wmt/wmt15/resolve/main/training-parallel-nc-v10.tgz",
269
  path=("news-commentary-v10.{src}-en.{src}", "news-commentary-v10.{src}-en.en"),
270
  ),
271
  SubDataset(
272
  name="newscommentary_v11",
273
  target="en",
274
  sources={"cs", "de", "ru"},
275
- url="https://huggingface.co/datasets/wmt/wmt16/resolve/main/translation-task/training-parallel-nc-v11.tgz",
276
  path=(
277
  "training-parallel-nc-v11/news-commentary-v11.{src}-en.{src}",
278
  "training-parallel-nc-v11/news-commentary-v11.{src}-en.en",
@@ -282,14 +282,14 @@ _TRAIN_SUBSETS = [
282
  name="newscommentary_v12",
283
  target="en",
284
  sources={"cs", "de", "ru", "zh"},
285
- url="https://huggingface.co/datasets/wmt/wmt17/resolve/main/translation-task/training-parallel-nc-v12.tgz",
286
  path=("training/news-commentary-v12.{src}-en.{src}", "training/news-commentary-v12.{src}-en.en"),
287
  ),
288
  SubDataset(
289
  name="newscommentary_v13",
290
  target="en",
291
  sources={"cs", "de", "ru", "zh"},
292
- url="https://huggingface.co/datasets/wmt/wmt18/resolve/main/translation-task/training-parallel-nc-v13.tgz",
293
  path=(
294
  "training-parallel-nc-v13/news-commentary-v13.{src}-en.{src}",
295
  "training-parallel-nc-v13/news-commentary-v13.{src}-en.en",
@@ -313,14 +313,14 @@ _TRAIN_SUBSETS = [
313
  name="onlinebooks_v1",
314
  target="en",
315
  sources={"lv"},
316
- url="https://huggingface.co/datasets/wmt/wmt17/resolve/main/translation-task/books.lv-en.v1.tgz",
317
  path=("farewell/farewell.lv", "farewell/farewell.en"),
318
  ),
319
  SubDataset(
320
  name="paracrawl_v1",
321
  target="en",
322
  sources={"cs", "de", "et", "fi", "ru"},
323
- url="https://s3.amazonaws.com/web-language-models/paracrawl/release1/paracrawl-release1.en-{src}.zipporah0-dedup-clean.tgz",
324
  path=(
325
  "paracrawl-release1.en-{src}.zipporah0-dedup-clean.{src}",
326
  "paracrawl-release1.en-{src}.zipporah0-dedup-clean.en",
@@ -330,7 +330,7 @@ _TRAIN_SUBSETS = [
330
  name="paracrawl_v1_ru",
331
  target="en",
332
  sources={"ru"},
333
- url="https://s3.amazonaws.com/web-language-models/paracrawl/release1/paracrawl-release1.en-ru.zipporah0-dedup-clean.tgz",
334
  path=(
335
  "paracrawl-release1.en-ru.zipporah0-dedup-clean.ru",
336
  "paracrawl-release1.en-ru.zipporah0-dedup-clean.en",
@@ -357,7 +357,7 @@ _TRAIN_SUBSETS = [
357
  name="rapid_2016",
358
  target="en",
359
  sources={"de", "et", "fi"},
360
- url="https://huggingface.co/datasets/wmt/wmt18/resolve/main/translation-task/rapid2016.tgz",
361
  path=("rapid2016.{0}-{1}.{src}", "rapid2016.{0}-{1}.en"),
362
  ),
363
  SubDataset(
@@ -385,21 +385,21 @@ _TRAIN_SUBSETS = [
385
  name="uncorpus_v1",
386
  target="en",
387
  sources={"ru", "zh"},
388
- url="https://huggingface.co/datasets/wmt/uncorpus/resolve/main/UNv1.0.en-{src}.tar.gz",
389
  path=("en-{src}/UNv1.0.en-{src}.{src}", "en-{src}/UNv1.0.en-{src}.en"),
390
  ),
391
  SubDataset(
392
  name="wikiheadlines_fi",
393
  target="en",
394
  sources={"fi"},
395
- url="https://huggingface.co/datasets/wmt/wmt15/resolve/main/wiki-titles.tgz",
396
  path="wiki/fi-en/titles.fi-en",
397
  ),
398
  SubDataset(
399
  name="wikiheadlines_hi",
400
  target="en",
401
  sources={"hi"},
402
- url="https://huggingface.co/datasets/wmt/wmt14/resolve/main/wiki-titles.tgz",
403
  path="wiki/hi-en/wiki-titles.hi-en",
404
  ),
405
  SubDataset(
@@ -407,7 +407,7 @@ _TRAIN_SUBSETS = [
407
  name="wikiheadlines_ru",
408
  target="en",
409
  sources={"ru"},
410
- url="https://huggingface.co/datasets/wmt/wmt15/resolve/main/wiki-titles.tgz",
411
  path="wiki/ru-en/wiki.ru-en",
412
  ),
413
  SubDataset(
@@ -431,7 +431,7 @@ _TRAIN_SUBSETS = [
431
  name=ss,
432
  target="en",
433
  sources={"zh"},
434
- url="ftp://cwmt-wmt:cwmt-wmt@datasets.nju.edu.cn/parallel/%s.zip" % ss,
435
  path=("%s/*_c[hn].txt" % ss, "%s/*_en.txt" % ss),
436
  )
437
  for ss in CWMT_SUBSET_NAMES
@@ -442,175 +442,175 @@ _DEV_SUBSETS = [
442
  name="euelections_dev2019",
443
  target="de",
444
  sources={"fr"},
445
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
446
  path=("dev/euelections_dev2019.fr-de.src.fr", "dev/euelections_dev2019.fr-de.tgt.de"),
447
  ),
448
  SubDataset(
449
  name="newsdev2014",
450
  target="en",
451
  sources={"hi"},
452
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
453
  path=("dev/newsdev2014.hi", "dev/newsdev2014.en"),
454
  ),
455
  SubDataset(
456
  name="newsdev2015",
457
  target="en",
458
  sources={"fi"},
459
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
460
  path=("dev/newsdev2015-fien-src.{src}.sgm", "dev/newsdev2015-fien-ref.en.sgm"),
461
  ),
462
  SubDataset(
463
  name="newsdiscussdev2015",
464
  target="en",
465
  sources={"ro", "tr"},
466
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
467
  path=("dev/newsdiscussdev2015-{src}en-src.{src}.sgm", "dev/newsdiscussdev2015-{src}en-ref.en.sgm"),
468
  ),
469
  SubDataset(
470
  name="newsdev2016",
471
  target="en",
472
  sources={"ro", "tr"},
473
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
474
  path=("dev/newsdev2016-{src}en-src.{src}.sgm", "dev/newsdev2016-{src}en-ref.en.sgm"),
475
  ),
476
  SubDataset(
477
  name="newsdev2017",
478
  target="en",
479
  sources={"lv", "zh"},
480
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
481
  path=("dev/newsdev2017-{src}en-src.{src}.sgm", "dev/newsdev2017-{src}en-ref.en.sgm"),
482
  ),
483
  SubDataset(
484
  name="newsdev2018",
485
  target="en",
486
  sources={"et"},
487
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
488
  path=("dev/newsdev2018-{src}en-src.{src}.sgm", "dev/newsdev2018-{src}en-ref.en.sgm"),
489
  ),
490
  SubDataset(
491
  name="newsdev2019",
492
  target="en",
493
  sources={"gu", "kk", "lt"},
494
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
495
  path=("dev/newsdev2019-{src}en-src.{src}.sgm", "dev/newsdev2019-{src}en-ref.en.sgm"),
496
  ),
497
  SubDataset(
498
  name="newsdiscussdev2015",
499
  target="en",
500
  sources={"fr"},
501
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
502
  path=("dev/newsdiscussdev2015-{src}en-src.{src}.sgm", "dev/newsdiscussdev2015-{src}en-ref.en.sgm"),
503
  ),
504
  SubDataset(
505
  name="newsdiscusstest2015",
506
  target="en",
507
  sources={"fr"},
508
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
509
  path=("dev/newsdiscusstest2015-{src}en-src.{src}.sgm", "dev/newsdiscusstest2015-{src}en-ref.en.sgm"),
510
  ),
511
  SubDataset(
512
  name="newssyscomb2009",
513
  target="en",
514
  sources={"cs", "de", "es", "fr"},
515
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
516
  path=("dev/newssyscomb2009.{src}", "dev/newssyscomb2009.en"),
517
  ),
518
  SubDataset(
519
  name="newstest2008",
520
  target="en",
521
  sources={"cs", "de", "es", "fr", "hu"},
522
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
523
  path=("dev/news-test2008.{src}", "dev/news-test2008.en"),
524
  ),
525
  SubDataset(
526
  name="newstest2009",
527
  target="en",
528
  sources={"cs", "de", "es", "fr"},
529
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
530
  path=("dev/newstest2009.{src}", "dev/newstest2009.en"),
531
  ),
532
  SubDataset(
533
  name="newstest2010",
534
  target="en",
535
  sources={"cs", "de", "es", "fr"},
536
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
537
  path=("dev/newstest2010.{src}", "dev/newstest2010.en"),
538
  ),
539
  SubDataset(
540
  name="newstest2011",
541
  target="en",
542
  sources={"cs", "de", "es", "fr"},
543
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
544
  path=("dev/newstest2011.{src}", "dev/newstest2011.en"),
545
  ),
546
  SubDataset(
547
  name="newstest2012",
548
  target="en",
549
  sources={"cs", "de", "es", "fr", "ru"},
550
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
551
  path=("dev/newstest2012.{src}", "dev/newstest2012.en"),
552
  ),
553
  SubDataset(
554
  name="newstest2013",
555
  target="en",
556
  sources={"cs", "de", "es", "fr", "ru"},
557
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
558
  path=("dev/newstest2013.{src}", "dev/newstest2013.en"),
559
  ),
560
  SubDataset(
561
  name="newstest2014",
562
  target="en",
563
  sources={"cs", "de", "es", "fr", "hi", "ru"},
564
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
565
  path=("dev/newstest2014-{src}en-src.{src}.sgm", "dev/newstest2014-{src}en-ref.en.sgm"),
566
  ),
567
  SubDataset(
568
  name="newstest2015",
569
  target="en",
570
  sources={"cs", "de", "fi", "ru"},
571
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
572
  path=("dev/newstest2015-{src}en-src.{src}.sgm", "dev/newstest2015-{src}en-ref.en.sgm"),
573
  ),
574
  SubDataset(
575
  name="newsdiscusstest2015",
576
  target="en",
577
  sources={"fr"},
578
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
579
  path=("dev/newsdiscusstest2015-{src}en-src.{src}.sgm", "dev/newsdiscusstest2015-{src}en-ref.en.sgm"),
580
  ),
581
  SubDataset(
582
  name="newstest2016",
583
  target="en",
584
  sources={"cs", "de", "fi", "ro", "ru", "tr"},
585
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
586
  path=("dev/newstest2016-{src}en-src.{src}.sgm", "dev/newstest2016-{src}en-ref.en.sgm"),
587
  ),
588
  SubDataset(
589
  name="newstestB2016",
590
  target="en",
591
  sources={"fi"},
592
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
593
  path=("dev/newstestB2016-enfi-ref.{src}.sgm", "dev/newstestB2016-enfi-src.en.sgm"),
594
  ),
595
  SubDataset(
596
  name="newstest2017",
597
  target="en",
598
  sources={"cs", "de", "fi", "lv", "ru", "tr", "zh"},
599
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
600
  path=("dev/newstest2017-{src}en-src.{src}.sgm", "dev/newstest2017-{src}en-ref.en.sgm"),
601
  ),
602
  SubDataset(
603
  name="newstestB2017",
604
  target="en",
605
  sources={"fi"},
606
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
607
  path=("dev/newstestB2017-fien-src.fi.sgm", "dev/newstestB2017-fien-ref.en.sgm"),
608
  ),
609
  SubDataset(
610
  name="newstest2018",
611
  target="en",
612
  sources={"cs", "de", "et", "fi", "ru", "tr", "zh"},
613
- url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
614
  path=("dev/newstest2018-{src}en-src.{src}.sgm", "dev/newstest2018-{src}en-ref.en.sgm"),
615
  ),
616
  ]
@@ -658,9 +658,7 @@ class WmtConfig(datasets.BuilderConfig):
658
  # TODO(PVP): remove when manual dir works
659
  # +++++++++++++++++++++
660
  if language_pair[1] in ["cs", "hi", "ru"]:
661
- assert NotImplementedError(
662
- "The dataset for {}-en is currently not fully supported.".format(language_pair[1])
663
- )
664
  # +++++++++++++++++++++
665
 
666
 
@@ -730,7 +728,7 @@ class Wmt(ABC, datasets.GeneratorBasedBuilder):
730
  if dataset.get_manual_dl_files(source):
731
  # TODO(PVP): following two lines skip configs that are incomplete for now
732
  # +++++++++++++++++++++
733
- logger.info("Skipping {} for now. Incomplete dataset for {}".format(dataset.name, self.config.name))
734
  continue
735
  # +++++++++++++++++++++
736
 
@@ -741,9 +739,7 @@ class Wmt(ABC, datasets.GeneratorBasedBuilder):
741
  ]
742
  assert all(
743
  os.path.exists(path) for path in manual_paths
744
- ), "For {0}, you must manually download the following file(s) from {1} and place them in {2}: {3}".format(
745
- dataset.name, dataset.get_url(source), dl_manager.manual_dir, ", ".join(manual_dl_files)
746
- )
747
 
748
  # set manual path for correct subset
749
  manual_paths_dict[ss_name] = manual_paths
@@ -779,20 +775,31 @@ class Wmt(ABC, datasets.GeneratorBasedBuilder):
779
  for ex_dir, rel_path in zip(extract_dirs, rel_paths)
780
  ]
781
 
 
 
 
 
 
 
 
782
  for ss_name in split_subsets:
783
  # TODO(PVP) remove following five lines when manual data works
784
  # +++++++++++++++++++++
785
  dataset = DATASET_MAP[ss_name]
786
  source, _ = self.config.language_pair
787
  if dataset.get_manual_dl_files(source):
788
- logger.info("Skipping {} for now. Incomplete dataset for {}".format(dataset.name, self.config.name))
789
  continue
790
  # +++++++++++++++++++++
791
 
792
  logger.info("Generating examples from: %s", ss_name)
 
793
  dataset = DATASET_MAP[ss_name]
794
  extract_dirs = extraction_map[ss_name]
795
  files = _get_local_paths(dataset, extract_dirs)
 
 
 
796
 
797
  if ss_name.startswith("czeng"):
798
  if ss_name.endswith("16pre"):
@@ -809,8 +816,9 @@ class Wmt(ABC, datasets.GeneratorBasedBuilder):
809
  sub_generator = _parse_frde_bitext
810
  else:
811
  sub_generator = _parse_parallel_sentences
 
812
  elif len(files) == 1:
813
- fname = files[0]
814
  # Note: Due to formatting used by `download_manager`, the file
815
  # extension may not be at the end of the file path.
816
  if ".tsv" in fname:
@@ -830,28 +838,33 @@ class Wmt(ABC, datasets.GeneratorBasedBuilder):
830
  else:
831
  raise ValueError("Invalid number of files: %d" % len(files))
832
 
833
- for sub_key, ex in sub_generator(*files):
834
  if not all(ex.values()):
835
  continue
836
  # TODO(adarob): Add subset feature.
837
  # ex["subset"] = subset
838
- key = "{}/{}".format(ss_name, sub_key)
839
  if with_translation is True:
840
  ex = {"translation": ex}
841
  yield key, ex
842
 
843
 
844
- def _parse_parallel_sentences(f1, f2):
845
  """Returns examples from parallel SGML or text files, which may be gzipped."""
846
 
847
- def _parse_text(path):
848
  """Returns the sentences from a single text file, which may be gzipped."""
849
- split_path = path.split(".")
850
 
851
  if split_path[-1] == "gz":
852
  lang = split_path[-2]
853
- with open(path, "rb") as f, gzip.GzipFile(fileobj=f) as g:
854
- return g.read().decode("utf-8").split("\n"), lang
 
 
 
 
 
855
 
856
  if split_path[-1] == "txt":
857
  # CWMT
@@ -859,25 +872,32 @@ def _parse_parallel_sentences(f1, f2):
859
  lang = "zh" if lang in ("ch", "cn") else lang
860
  else:
861
  lang = split_path[-1]
862
- with open(path, "rb") as f:
863
- return f.read().decode("utf-8").split("\n"), lang
864
 
865
- def _parse_sgm(path):
 
 
 
 
 
 
 
866
  """Returns sentences from a single SGML file."""
867
- lang = path.split(".")[-2]
868
- sentences = []
869
  # Note: We can't use the XML parser since some of the files are badly
870
  # formatted.
871
  seg_re = re.compile(r"<seg id=\"\d+\">(.*)</seg>")
872
- with open(path, encoding="utf-8") as f:
873
- for line in f:
874
- seg_match = re.match(seg_re, line)
875
- if seg_match:
876
- assert len(seg_match.groups()) == 1
877
- sentences.append(seg_match.groups()[0])
878
- return sentences, lang
879
 
880
- parse_file = _parse_sgm if f1.endswith(".sgm") else _parse_text
 
 
 
 
 
 
 
 
 
 
881
 
882
  # Some datasets (e.g., CWMT) contain multiple parallel files specified with
883
  # a wildcard. We sort both sets to align them and parse them one by one.
@@ -893,34 +913,19 @@ def _parse_parallel_sentences(f1, f2):
893
  )
894
 
895
  for f_id, (f1_i, f2_i) in enumerate(zip(sorted(f1_files), sorted(f2_files))):
896
- l1_sentences, l1 = parse_file(f1_i)
897
- l2_sentences, l2 = parse_file(f2_i)
898
-
899
- assert len(l1_sentences) == len(l2_sentences), "Sizes do not match: %d vs %d for %s vs %s." % (
900
- len(l1_sentences),
901
- len(l2_sentences),
902
- f1_i,
903
- f2_i,
904
- )
905
 
906
  for line_id, (s1, s2) in enumerate(zip(l1_sentences, l2_sentences)):
907
- key = "{}/{}".format(f_id, line_id)
908
  yield key, {l1: s1, l2: s2}
909
 
910
 
911
  def _parse_frde_bitext(fr_path, de_path):
912
- with open(fr_path, encoding="utf-8") as f:
913
- fr_sentences = f.read().split("\n")
914
- with open(de_path, encoding="utf-8") as f:
915
- de_sentences = f.read().split("\n")
916
- assert len(fr_sentences) == len(de_sentences), "Sizes do not match: %d vs %d for %s vs %s." % (
917
- len(fr_sentences),
918
- len(de_sentences),
919
- fr_path,
920
- de_path,
921
- )
922
- for line_id, (s1, s2) in enumerate(zip(fr_sentences, de_sentences)):
923
- yield line_id, {"fr": s1, "de": s2}
924
 
925
 
926
  def _parse_tmx(path):
@@ -997,7 +1002,7 @@ def _parse_czeng(*paths, **kwargs):
997
  block_match = re.match(re_block, id_)
998
  if block_match and block_match.groups()[0] in bad_blocks:
999
  continue
1000
- sub_key = "{}/{}".format(filename, line_id)
1001
  yield sub_key, {
1002
  "cs": cs.strip(),
1003
  "en": en.strip(),
 
96
  def _inject_language(self, src, strings):
97
  """Injects languages into (potentially) template strings."""
98
  if src not in self.sources:
99
+ raise ValueError(f"Invalid source for '{self.name}': {src}")
100
 
101
  def _format_string(s):
102
  if "{0}" in s and "{1}" and "{src}" in s:
 
127
  name="commoncrawl",
128
  target="en", # fr-de pair in commoncrawl_frde
129
  sources={"cs", "de", "es", "fr", "ru"},
130
+ url="https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-commoncrawl.zip",
131
  path=("commoncrawl.{src}-en.{src}", "commoncrawl.{src}-en.en"),
132
  ),
133
  SubDataset(
 
184
  name="dcep_v1",
185
  target="en",
186
  sources={"lv"},
187
+ url="https://huggingface.co/datasets/wmt/wmt17/resolve/main-zip/translation-task/dcep.lv-en.v1.zip",
188
  path=("dcep.en-lv/dcep.lv", "dcep.en-lv/dcep.en"),
189
  ),
190
  SubDataset(
191
  name="europarl_v7",
192
  target="en",
193
  sources={"cs", "de", "es", "fr"},
194
+ url="https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-europarl-v7.zip",
195
  path=("training/europarl-v7.{src}-en.{src}", "training/europarl-v7.{src}-en.en"),
196
  ),
197
  SubDataset(
 
208
  name="europarl_v8_18",
209
  target="en",
210
  sources={"et", "fi"},
211
+ url="https://huggingface.co/datasets/wmt/wmt18/resolve/main-zip/translation-task/training-parallel-ep-v8.zip",
212
  path=("training/europarl-v8.{src}-en.{src}", "training/europarl-v8.{src}-en.en"),
213
  ),
214
  SubDataset(
215
  name="europarl_v8_16",
216
  target="en",
217
  sources={"fi", "ro"},
218
+ url="https://huggingface.co/datasets/wmt/wmt16/resolve/main-zip/translation-task/training-parallel-ep-v8.zip",
219
  path=("training-parallel-ep-v8/europarl-v8.{src}-en.{src}", "training-parallel-ep-v8/europarl-v8.{src}-en.en"),
220
  ),
221
  SubDataset(
 
229
  name="gigafren",
230
  target="en",
231
  sources={"fr"},
232
+ url="https://huggingface.co/datasets/wmt/wmt10/resolve/main-zip/training-giga-fren.zip",
233
  path=("giga-fren.release2.fixed.fr.gz", "giga-fren.release2.fixed.en.gz"),
234
  ),
235
  SubDataset(
 
244
  name="leta_v1",
245
  target="en",
246
  sources={"lv"},
247
+ url="https://huggingface.co/datasets/wmt/wmt17/resolve/main-zip/translation-task/leta.v1.zip",
248
  path=("LETA-lv-en/leta.lv", "LETA-lv-en/leta.en"),
249
  ),
250
  SubDataset(
251
  name="multiun",
252
  target="en",
253
  sources={"es", "fr"},
254
+ url="https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-un.zip",
255
  path=("un/undoc.2000.{src}-en.{src}", "un/undoc.2000.{src}-en.en"),
256
  ),
257
  SubDataset(
258
  name="newscommentary_v9",
259
  target="en",
260
  sources={"cs", "de", "fr", "ru"},
261
+ url="https://huggingface.co/datasets/wmt/wmt14/resolve/main-zip/training-parallel-nc-v9.zip",
262
  path=("training/news-commentary-v9.{src}-en.{src}", "training/news-commentary-v9.{src}-en.en"),
263
  ),
264
  SubDataset(
265
  name="newscommentary_v10",
266
  target="en",
267
  sources={"cs", "de", "fr", "ru"},
268
+ url="https://huggingface.co/datasets/wmt/wmt15/resolve/main-zip/training-parallel-nc-v10.zip",
269
  path=("news-commentary-v10.{src}-en.{src}", "news-commentary-v10.{src}-en.en"),
270
  ),
271
  SubDataset(
272
  name="newscommentary_v11",
273
  target="en",
274
  sources={"cs", "de", "ru"},
275
+ url="https://huggingface.co/datasets/wmt/wmt16/resolve/main-zip/translation-task/training-parallel-nc-v11.zip",
276
  path=(
277
  "training-parallel-nc-v11/news-commentary-v11.{src}-en.{src}",
278
  "training-parallel-nc-v11/news-commentary-v11.{src}-en.en",
 
282
  name="newscommentary_v12",
283
  target="en",
284
  sources={"cs", "de", "ru", "zh"},
285
+ url="https://huggingface.co/datasets/wmt/wmt17/resolve/main-zip/translation-task/training-parallel-nc-v12.zip",
286
  path=("training/news-commentary-v12.{src}-en.{src}", "training/news-commentary-v12.{src}-en.en"),
287
  ),
288
  SubDataset(
289
  name="newscommentary_v13",
290
  target="en",
291
  sources={"cs", "de", "ru", "zh"},
292
+ url="https://huggingface.co/datasets/wmt/wmt18/resolve/main-zip/translation-task/training-parallel-nc-v13.zip",
293
  path=(
294
  "training-parallel-nc-v13/news-commentary-v13.{src}-en.{src}",
295
  "training-parallel-nc-v13/news-commentary-v13.{src}-en.en",
 
313
  name="onlinebooks_v1",
314
  target="en",
315
  sources={"lv"},
316
+ url="https://huggingface.co/datasets/wmt/wmt17/resolve/main-zip/translation-task/books.lv-en.v1.zip",
317
  path=("farewell/farewell.lv", "farewell/farewell.en"),
318
  ),
319
  SubDataset(
320
  name="paracrawl_v1",
321
  target="en",
322
  sources={"cs", "de", "et", "fi", "ru"},
323
+ url="https://s3.amazonaws.com/web-language-models/paracrawl/release1/paracrawl-release1.en-{src}.zipporah0-dedup-clean.tgz", # TODO(QL): use gzip for streaming
324
  path=(
325
  "paracrawl-release1.en-{src}.zipporah0-dedup-clean.{src}",
326
  "paracrawl-release1.en-{src}.zipporah0-dedup-clean.en",
 
330
  name="paracrawl_v1_ru",
331
  target="en",
332
  sources={"ru"},
333
+ url="https://s3.amazonaws.com/web-language-models/paracrawl/release1/paracrawl-release1.en-ru.zipporah0-dedup-clean.tgz", # TODO(QL): use gzip for streaming
334
  path=(
335
  "paracrawl-release1.en-ru.zipporah0-dedup-clean.ru",
336
  "paracrawl-release1.en-ru.zipporah0-dedup-clean.en",
 
357
  name="rapid_2016",
358
  target="en",
359
  sources={"de", "et", "fi"},
360
+ url="https://huggingface.co/datasets/wmt/wmt18/resolve/main-zip/translation-task/rapid2016.zip",
361
  path=("rapid2016.{0}-{1}.{src}", "rapid2016.{0}-{1}.en"),
362
  ),
363
  SubDataset(
 
385
  name="uncorpus_v1",
386
  target="en",
387
  sources={"ru", "zh"},
388
+ url="https://huggingface.co/datasets/wmt/uncorpus/resolve/main-zip/UNv1.0.en-{src}.zip",
389
  path=("en-{src}/UNv1.0.en-{src}.{src}", "en-{src}/UNv1.0.en-{src}.en"),
390
  ),
391
  SubDataset(
392
  name="wikiheadlines_fi",
393
  target="en",
394
  sources={"fi"},
395
+ url="https://huggingface.co/datasets/wmt/wmt15/resolve/main-zip/wiki-titles.zip",
396
  path="wiki/fi-en/titles.fi-en",
397
  ),
398
  SubDataset(
399
  name="wikiheadlines_hi",
400
  target="en",
401
  sources={"hi"},
402
+ url="https://huggingface.co/datasets/wmt/wmt14/resolve/main-zip/wiki-titles.zip",
403
  path="wiki/hi-en/wiki-titles.hi-en",
404
  ),
405
  SubDataset(
 
407
  name="wikiheadlines_ru",
408
  target="en",
409
  sources={"ru"},
410
+ url="https://huggingface.co/datasets/wmt/wmt15/resolve/main-zip/wiki-titles.zip",
411
  path="wiki/ru-en/wiki.ru-en",
412
  ),
413
  SubDataset(
 
431
  name=ss,
432
  target="en",
433
  sources={"zh"},
434
+ url="http://www.hackcha.cn/cwmt_data//%s.zip" % ss,
435
  path=("%s/*_c[hn].txt" % ss, "%s/*_en.txt" % ss),
436
  )
437
  for ss in CWMT_SUBSET_NAMES
 
442
  name="euelections_dev2019",
443
  target="de",
444
  sources={"fr"},
445
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
446
  path=("dev/euelections_dev2019.fr-de.src.fr", "dev/euelections_dev2019.fr-de.tgt.de"),
447
  ),
448
  SubDataset(
449
  name="newsdev2014",
450
  target="en",
451
  sources={"hi"},
452
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
453
  path=("dev/newsdev2014.hi", "dev/newsdev2014.en"),
454
  ),
455
  SubDataset(
456
  name="newsdev2015",
457
  target="en",
458
  sources={"fi"},
459
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
460
  path=("dev/newsdev2015-fien-src.{src}.sgm", "dev/newsdev2015-fien-ref.en.sgm"),
461
  ),
462
  SubDataset(
463
  name="newsdiscussdev2015",
464
  target="en",
465
  sources={"ro", "tr"},
466
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
467
  path=("dev/newsdiscussdev2015-{src}en-src.{src}.sgm", "dev/newsdiscussdev2015-{src}en-ref.en.sgm"),
468
  ),
469
  SubDataset(
470
  name="newsdev2016",
471
  target="en",
472
  sources={"ro", "tr"},
473
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
474
  path=("dev/newsdev2016-{src}en-src.{src}.sgm", "dev/newsdev2016-{src}en-ref.en.sgm"),
475
  ),
476
  SubDataset(
477
  name="newsdev2017",
478
  target="en",
479
  sources={"lv", "zh"},
480
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
481
  path=("dev/newsdev2017-{src}en-src.{src}.sgm", "dev/newsdev2017-{src}en-ref.en.sgm"),
482
  ),
483
  SubDataset(
484
  name="newsdev2018",
485
  target="en",
486
  sources={"et"},
487
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
488
  path=("dev/newsdev2018-{src}en-src.{src}.sgm", "dev/newsdev2018-{src}en-ref.en.sgm"),
489
  ),
490
  SubDataset(
491
  name="newsdev2019",
492
  target="en",
493
  sources={"gu", "kk", "lt"},
494
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
495
  path=("dev/newsdev2019-{src}en-src.{src}.sgm", "dev/newsdev2019-{src}en-ref.en.sgm"),
496
  ),
497
  SubDataset(
498
  name="newsdiscussdev2015",
499
  target="en",
500
  sources={"fr"},
501
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
502
  path=("dev/newsdiscussdev2015-{src}en-src.{src}.sgm", "dev/newsdiscussdev2015-{src}en-ref.en.sgm"),
503
  ),
504
  SubDataset(
505
  name="newsdiscusstest2015",
506
  target="en",
507
  sources={"fr"},
508
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
509
  path=("dev/newsdiscusstest2015-{src}en-src.{src}.sgm", "dev/newsdiscusstest2015-{src}en-ref.en.sgm"),
510
  ),
511
  SubDataset(
512
  name="newssyscomb2009",
513
  target="en",
514
  sources={"cs", "de", "es", "fr"},
515
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
516
  path=("dev/newssyscomb2009.{src}", "dev/newssyscomb2009.en"),
517
  ),
518
  SubDataset(
519
  name="newstest2008",
520
  target="en",
521
  sources={"cs", "de", "es", "fr", "hu"},
522
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
523
  path=("dev/news-test2008.{src}", "dev/news-test2008.en"),
524
  ),
525
  SubDataset(
526
  name="newstest2009",
527
  target="en",
528
  sources={"cs", "de", "es", "fr"},
529
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
530
  path=("dev/newstest2009.{src}", "dev/newstest2009.en"),
531
  ),
532
  SubDataset(
533
  name="newstest2010",
534
  target="en",
535
  sources={"cs", "de", "es", "fr"},
536
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
537
  path=("dev/newstest2010.{src}", "dev/newstest2010.en"),
538
  ),
539
  SubDataset(
540
  name="newstest2011",
541
  target="en",
542
  sources={"cs", "de", "es", "fr"},
543
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
544
  path=("dev/newstest2011.{src}", "dev/newstest2011.en"),
545
  ),
546
  SubDataset(
547
  name="newstest2012",
548
  target="en",
549
  sources={"cs", "de", "es", "fr", "ru"},
550
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
551
  path=("dev/newstest2012.{src}", "dev/newstest2012.en"),
552
  ),
553
  SubDataset(
554
  name="newstest2013",
555
  target="en",
556
  sources={"cs", "de", "es", "fr", "ru"},
557
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
558
  path=("dev/newstest2013.{src}", "dev/newstest2013.en"),
559
  ),
560
  SubDataset(
561
  name="newstest2014",
562
  target="en",
563
  sources={"cs", "de", "es", "fr", "hi", "ru"},
564
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
565
  path=("dev/newstest2014-{src}en-src.{src}.sgm", "dev/newstest2014-{src}en-ref.en.sgm"),
566
  ),
567
  SubDataset(
568
  name="newstest2015",
569
  target="en",
570
  sources={"cs", "de", "fi", "ru"},
571
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
572
  path=("dev/newstest2015-{src}en-src.{src}.sgm", "dev/newstest2015-{src}en-ref.en.sgm"),
573
  ),
574
  SubDataset(
575
  name="newsdiscusstest2015",
576
  target="en",
577
  sources={"fr"},
578
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
579
  path=("dev/newsdiscusstest2015-{src}en-src.{src}.sgm", "dev/newsdiscusstest2015-{src}en-ref.en.sgm"),
580
  ),
581
  SubDataset(
582
  name="newstest2016",
583
  target="en",
584
  sources={"cs", "de", "fi", "ro", "ru", "tr"},
585
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
586
  path=("dev/newstest2016-{src}en-src.{src}.sgm", "dev/newstest2016-{src}en-ref.en.sgm"),
587
  ),
588
  SubDataset(
589
  name="newstestB2016",
590
  target="en",
591
  sources={"fi"},
592
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
593
  path=("dev/newstestB2016-enfi-ref.{src}.sgm", "dev/newstestB2016-enfi-src.en.sgm"),
594
  ),
595
  SubDataset(
596
  name="newstest2017",
597
  target="en",
598
  sources={"cs", "de", "fi", "lv", "ru", "tr", "zh"},
599
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
600
  path=("dev/newstest2017-{src}en-src.{src}.sgm", "dev/newstest2017-{src}en-ref.en.sgm"),
601
  ),
602
  SubDataset(
603
  name="newstestB2017",
604
  target="en",
605
  sources={"fi"},
606
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
607
  path=("dev/newstestB2017-fien-src.fi.sgm", "dev/newstestB2017-fien-ref.en.sgm"),
608
  ),
609
  SubDataset(
610
  name="newstest2018",
611
  target="en",
612
  sources={"cs", "de", "et", "fi", "ru", "tr", "zh"},
613
+ url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
614
  path=("dev/newstest2018-{src}en-src.{src}.sgm", "dev/newstest2018-{src}en-ref.en.sgm"),
615
  ),
616
  ]
 
658
  # TODO(PVP): remove when manual dir works
659
  # +++++++++++++++++++++
660
  if language_pair[1] in ["cs", "hi", "ru"]:
661
+ assert NotImplementedError(f"The dataset for {language_pair[1]}-en is currently not fully supported.")
 
 
662
  # +++++++++++++++++++++
663
 
664
 
 
728
  if dataset.get_manual_dl_files(source):
729
  # TODO(PVP): following two lines skip configs that are incomplete for now
730
  # +++++++++++++++++++++
731
+ logger.info(f"Skipping {dataset.name} for now. Incomplete dataset for {self.config.name}")
732
  continue
733
  # +++++++++++++++++++++
734
 
 
739
  ]
740
  assert all(
741
  os.path.exists(path) for path in manual_paths
742
+ ), 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)}"
 
 
743
 
744
  # set manual path for correct subset
745
  manual_paths_dict[ss_name] = manual_paths
 
775
  for ex_dir, rel_path in zip(extract_dirs, rel_paths)
776
  ]
777
 
778
+ def _get_filenames(dataset):
779
+ rel_paths = dataset.get_path(source)
780
+ urls = dataset.get_url(source)
781
+ if len(urls) == 1:
782
+ urls = urls * len(rel_paths)
783
+ return [rel_path if rel_path else os.path.basename(url) for url, rel_path in zip(urls, rel_paths)]
784
+
785
  for ss_name in split_subsets:
786
  # TODO(PVP) remove following five lines when manual data works
787
  # +++++++++++++++++++++
788
  dataset = DATASET_MAP[ss_name]
789
  source, _ = self.config.language_pair
790
  if dataset.get_manual_dl_files(source):
791
+ logger.info(f"Skipping {dataset.name} for now. Incomplete dataset for {self.config.name}")
792
  continue
793
  # +++++++++++++++++++++
794
 
795
  logger.info("Generating examples from: %s", ss_name)
796
+ print("Generating examples from: %s", ss_name)
797
  dataset = DATASET_MAP[ss_name]
798
  extract_dirs = extraction_map[ss_name]
799
  files = _get_local_paths(dataset, extract_dirs)
800
+ filenames = _get_filenames(dataset)
801
+
802
+ sub_generator_args = tuple(files)
803
 
804
  if ss_name.startswith("czeng"):
805
  if ss_name.endswith("16pre"):
 
816
  sub_generator = _parse_frde_bitext
817
  else:
818
  sub_generator = _parse_parallel_sentences
819
+ sub_generator_args += tuple(filenames)
820
  elif len(files) == 1:
821
+ fname = filenames[0]
822
  # Note: Due to formatting used by `download_manager`, the file
823
  # extension may not be at the end of the file path.
824
  if ".tsv" in fname:
 
838
  else:
839
  raise ValueError("Invalid number of files: %d" % len(files))
840
 
841
+ for sub_key, ex in sub_generator(*sub_generator_args):
842
  if not all(ex.values()):
843
  continue
844
  # TODO(adarob): Add subset feature.
845
  # ex["subset"] = subset
846
+ key = f"{ss_name}/{sub_key}"
847
  if with_translation is True:
848
  ex = {"translation": ex}
849
  yield key, ex
850
 
851
 
852
+ def _parse_parallel_sentences(f1, f2, filename1, filename2):
853
  """Returns examples from parallel SGML or text files, which may be gzipped."""
854
 
855
+ def _parse_text(path, original_filename):
856
  """Returns the sentences from a single text file, which may be gzipped."""
857
+ split_path = original_filename.split(".")
858
 
859
  if split_path[-1] == "gz":
860
  lang = split_path[-2]
861
+
862
+ def gen():
863
+ with open(path, "rb") as f, gzip.GzipFile(fileobj=f) as g:
864
+ for line in g:
865
+ yield line.decode("utf-8").rstrip()
866
+
867
+ return gen(), lang
868
 
869
  if split_path[-1] == "txt":
870
  # CWMT
 
872
  lang = "zh" if lang in ("ch", "cn") else lang
873
  else:
874
  lang = split_path[-1]
 
 
875
 
876
+ def gen():
877
+ with open(path, "rb") as f:
878
+ for line in f:
879
+ yield line.decode("utf-8").rstrip()
880
+
881
+ return gen(), lang
882
+
883
+ def _parse_sgm(path, original_filename):
884
  """Returns sentences from a single SGML file."""
885
+ lang = original_filename.split(".")[-2]
 
886
  # Note: We can't use the XML parser since some of the files are badly
887
  # formatted.
888
  seg_re = re.compile(r"<seg id=\"\d+\">(.*)</seg>")
 
 
 
 
 
 
 
889
 
890
+ def gen():
891
+ with open(path, encoding="utf-8") as f:
892
+ for line in f:
893
+ seg_match = re.match(seg_re, line)
894
+ if seg_match:
895
+ assert len(seg_match.groups()) == 1
896
+ yield seg_match.groups()[0]
897
+
898
+ return gen(), lang
899
+
900
+ parse_file = _parse_sgm if os.path.basename(f1).endswith(".sgm") else _parse_text
901
 
902
  # Some datasets (e.g., CWMT) contain multiple parallel files specified with
903
  # a wildcard. We sort both sets to align them and parse them one by one.
 
913
  )
914
 
915
  for f_id, (f1_i, f2_i) in enumerate(zip(sorted(f1_files), sorted(f2_files))):
916
+ l1_sentences, l1 = parse_file(f1_i, filename1)
917
+ l2_sentences, l2 = parse_file(f2_i, filename2)
 
 
 
 
 
 
 
918
 
919
  for line_id, (s1, s2) in enumerate(zip(l1_sentences, l2_sentences)):
920
+ key = f"{f_id}/{line_id}"
921
  yield key, {l1: s1, l2: s2}
922
 
923
 
924
  def _parse_frde_bitext(fr_path, de_path):
925
+ with open(fr_path, encoding="utf-8") as fr_f:
926
+ with open(de_path, encoding="utf-8") as de_f:
927
+ for line_id, (s1, s2) in enumerate(zip(fr_f, de_f)):
928
+ yield line_id, {"fr": s1.rstrip(), "de": s2.rstrip()}
 
 
 
 
 
 
 
 
929
 
930
 
931
  def _parse_tmx(path):
 
1002
  block_match = re.match(re_block, id_)
1003
  if block_match and block_match.groups()[0] in bad_blocks:
1004
  continue
1005
+ sub_key = f"{filename}/{line_id}"
1006
  yield sub_key, {
1007
  "cs": cs.strip(),
1008
  "en": en.strip(),