Update files from the datasets library (from 1.0.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.0.0

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zstandard filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

dataset_infos.json

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+{"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@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"}}, "supervised_keys": {"input": "cs", "output": "en"}, "builder_name": "wmt19", "config_name": "cs-en", "version": {"version_str": "1.0.0", "description": null, "datasets_version_to_prepare": 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": {"http://www.statmt.org/europarl/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"}, "http://www.statmt.org/wmt13/training-parallel-commoncrawl.tgz": {"num_bytes": 918311367, "checksum": "c7a74e2ea01ac6c920123108627e35278d4ccb5701e15428ffa34de86fa3a9e5"}, "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"}, "http://data.statmt.org/wikititles/v1/wikititles-v1.cs-en.tsv.gz": {"num_bytes": 5112423, "checksum": "54c9899b3cf897aaa520645436843d57e36ba9cce22f2c544a63a62493e18002"}, "http://data.statmt.org/wmt19/translation-task/dev.tgz": {"num_bytes": 38654961, "checksum": "7a7deccf82ebb05ba508dba5eb21356492224e8f630ec4f992132b029b4b25e7"}}, "download_size": 2018054617, "dataset_size": 1315568223, "size_in_bytes": 3333622840}}

dummy/cs-en/1.0.0/dummy_data.zip

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dummy/cs-en/1.0.0/dummy_data/dev.tgz/dev/newstest2013.cs

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+Just a test sentence.

dummy/cs-en/1.0.0/dummy_data/dev.tgz/dev/newstest2013.en

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+Just a test sentence.

dummy/cs-en/1.0.0/dummy_data/dev.tgz/dev/newstest2014-csen-ref.en.sgm

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+<seg id="1"> Test </seg>

dummy/cs-en/1.0.0/dummy_data/dev.tgz/dev/newstest2014-csen-src.cs.sgm

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dummy/cs-en/1.0.0/dummy_data/dev.tgz/dev/newstest2015-csen-ref.en.sgm

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dummy/cs-en/1.0.0/dummy_data/dev.tgz/dev/newstest2015-csen-src.cs.sgm

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dummy/cs-en/1.0.0/dummy_data/dev.tgz/dev/newstest2016-csen-ref.en.sgm

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dummy/cs-en/1.0.0/dummy_data/dev.tgz/dev/newstest2016-csen-src.cs.sgm

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dummy/cs-en/1.0.0/dummy_data/dev.tgz/dev/newstest2017-csen-ref.en.sgm

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dummy/cs-en/1.0.0/dummy_data/dev.tgz/dev/newstest2017-csen-src.cs.sgm

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dummy/cs-en/1.0.0/dummy_data/dev.tgz/dev/newstest2018-csen-ref.en.sgm

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+<seg id="1"> Test </seg>

dummy/cs-en/1.0.0/dummy_data/dev.tgz/dev/newstest2018-csen-src.cs.sgm

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+<seg id="1"> Test </seg>

dummy/cs-en/1.0.0/dummy_data/en-cs.bicleaner07.tmx.gz

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dummy/cs-en/1.0.0/dummy_data/europarl-v9.cs-en.tsv.gz

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dummy/cs-en/1.0.0/dummy_data/news-commentary-v14.cs-en.tsv.gz

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dummy/cs-en/1.0.0/dummy_data/paracrawl-release1.en-cs.zipporah0-dedup-clean.tgz/paracrawl-release1.en-cs.zipporah0-dedup-clean.cs

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dummy/cs-en/1.0.0/dummy_data/paracrawl-release1.en-cs.zipporah0-dedup-clean.tgz/paracrawl-release1.en-cs.zipporah0-dedup-clean.en

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dummy/cs-en/1.0.0/dummy_data/training-parallel-commoncrawl.tgz/commoncrawl.cs-en.cs

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+This is a test sentence.

dummy/cs-en/1.0.0/dummy_data/training-parallel-commoncrawl.tgz/commoncrawl.cs-en.en

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+This is a test sentence.

dummy/cs-en/1.0.0/dummy_data/training-parallel-europarl-v7.tgz/training/europarl-v7.cs-en.cs

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+This is a test sentence to pass the tests.

dummy/cs-en/1.0.0/dummy_data/training-parallel-europarl-v7.tgz/training/europarl-v7.cs-en.en

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dummy/cs-en/1.0.0/dummy_data/training-parallel-nc-v13.tgz/training-parallel-nc-v13/news-commentary-v13.cs-en.cs

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dummy/cs-en/1.0.0/dummy_data/training-parallel-nc-v13.tgz/training-parallel-nc-v13/news-commentary-v13.cs-en.en

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dummy/cs-en/1.0.0/dummy_data/wikititles-v1.cs-en.tsv.gz

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wmt19.py

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+# 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
+"""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

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+# 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."""
+
+from __future__ import absolute_import, division, print_function
+
+import codecs
+import functools
+import glob
+import gzip
+import itertools
+import logging
+import os
+import re
+import xml.etree.cElementTree as ElementTree
+from abc import ABC, abstractmethod
+
+import six
+
+import datasets
+
+
+_DESCRIPTION = """\
+Translate dataset based on the data from statmt.org.
+
+Versions exists for the different years using a combination of multiple data
+sources. The base `wmt_translate` allows you to create your own config to choose
+your own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.
+
+```
+config = datasets.wmt.WmtConfig(
+    version="0.0.1",
+    language_pair=("fr", "de"),
+    subsets={
+        datasets.Split.TRAIN: ["commoncrawl_frde"],
+        datasets.Split.VALIDATION: ["euelections_dev2019"],
+    },
+)
+builder = datasets.builder("wmt_translate", config=config)
+```
+
+"""
+
+
+CWMT_SUBSET_NAMES = ["casia2015", "casict2011", "casict2015", "datum2015", "datum2017", "neu2017"]
+
+
+class SubDataset(object):
+    """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, six.string_types) else path
+        self._urls = (url,) if isinstance(url, six.string_types) 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("Invalid source for '{0}': {1}".format(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="http://www.statmt.org/wmt13/training-parallel-commoncrawl.tgz",
+        path=("commoncrawl.{src}-en.{src}", "commoncrawl.{src}-en.en"),
+    ),
+    SubDataset(
+        name="commoncrawl_frde",
+        target="de",
+        sources={"fr"},
+        url=(
+            "http://data.statmt.org/wmt19/translation-task/fr-de/bitexts/commoncrawl.fr.gz",
+            "http://data.statmt.org/wmt19/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="http://data.statmt.org/wmt17/translation-task/dcep.lv-en.v1.tgz",
+        path=("dcep.en-lv/dcep.lv", "dcep.en-lv/dcep.en"),
+    ),
+    SubDataset(
+        name="europarl_v7",
+        target="en",
+        sources={"cs", "de", "es", "fr"},
+        url="http://www.statmt.org/wmt13/training-parallel-europarl-v7.tgz",
+        path=("training/europarl-v7.{src}-en.{src}", "training/europarl-v7.{src}-en.en"),
+    ),
+    SubDataset(
+        name="europarl_v7_frde",
+        target="de",
+        sources={"fr"},
+        url=(
+            "http://data.statmt.org/wmt19/translation-task/fr-de/bitexts/europarl-v7.fr.gz",
+            "http://data.statmt.org/wmt19/translation-task/fr-de/bitexts/europarl-v7.de.gz",
+        ),
+        path=("", ""),
+    ),
+    SubDataset(
+        name="europarl_v8_18",
+        target="en",
+        sources={"et", "fi"},
+        url="http://data.statmt.org/wmt18/translation-task/training-parallel-ep-v8.tgz",
+        path=("training/europarl-v8.{src}-en.{src}", "training/europarl-v8.{src}-en.en"),
+    ),
+    SubDataset(
+        name="europarl_v8_16",
+        target="en",
+        sources={"fi", "ro"},
+        url="http://data.statmt.org/wmt16/translation-task/training-parallel-ep-v8.tgz",
+        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="http://www.statmt.org/europarl/v9/training/europarl-v9.{src}-en.tsv.gz",
+        path="",
+    ),
+    SubDataset(
+        name="gigafren",
+        target="en",
+        sources={"fr"},
+        url="http://www.statmt.org/wmt10/training-giga-fren.tar",
+        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="http://data.statmt.org/wmt17/translation-task/leta.v1.tgz",
+        path=("LETA-lv-en/leta.lv", "LETA-lv-en/leta.en"),
+    ),
+    SubDataset(
+        name="multiun",
+        target="en",
+        sources={"es", "fr"},
+        url="http://www.statmt.org/wmt13/training-parallel-un.tgz",
+        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="http://www.statmt.org/wmt14/training-parallel-nc-v9.tgz",
+        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="http://www.statmt.org/wmt15/training-parallel-nc-v10.tgz",
+        path=("news-commentary-v10.{src}-en.{src}", "news-commentary-v10.{src}-en.en"),
+    ),
+    SubDataset(
+        name="newscommentary_v11",
+        target="en",
+        sources={"cs", "de", "ru"},
+        url="http://data.statmt.org/wmt16/translation-task/training-parallel-nc-v11.tgz",
+        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="http://data.statmt.org/wmt17/translation-task/training-parallel-nc-v12.tgz",
+        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="http://data.statmt.org/wmt18/translation-task/training-parallel-nc-v13.tgz",
+        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="http://data.statmt.org/wmt17/translation-task/books.lv-en.v1.tgz",
+        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",
+        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",
+        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=(
+            "http://data.statmt.org/wmt19/translation-task/fr-de/bitexts/de-fr.bicleaner07.de.gz",
+            "http://data.statmt.org/wmt19/translation-task/fr-de/bitexts/de-fr.bicleaner07.fr.gz",
+        ),
+        path=("", ""),
+    ),
+    SubDataset(
+        name="rapid_2016",
+        target="en",
+        sources={"de", "et", "fi"},
+        url="http://data.statmt.org/wmt18/translation-task/rapid2016.tgz",
+        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="http://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://storage.googleapis.com/tfdataset-data/downloadataset/uncorpus/UNv1.0.en-{src}.tar.gz",
+        path=("en-{src}/UNv1.0.en-{src}.{src}", "en-{src}/UNv1.0.en-{src}.en"),
+    ),
+    SubDataset(
+        name="wikiheadlines_fi",
+        target="en",
+        sources={"fi"},
+        url="http://www.statmt.org/wmt15/wiki-titles.tgz",
+        path="wiki/fi-en/titles.fi-en",
+    ),
+    SubDataset(
+        name="wikiheadlines_hi",
+        target="en",
+        sources={"hi"},
+        url="http://www.statmt.org/wmt14/wiki-titles.tgz",
+        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="http://www.statmt.org/wmt15/wiki-titles.tgz",
+        path="wiki/ru-en/wiki.ru-en",
+    ),
+    SubDataset(
+        name="wikititles_v1",
+        target="en",
+        sources={"cs", "de", "fi", "gu", "kk", "lt", "ru", "zh"},
+        url="http://data.statmt.org/wikititles/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="ftp://cwmt-wmt:cwmt-wmt@datasets.nju.edu.cn/parallel/%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="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        path=("dev/euelections_dev2019.fr-de.src.fr", "dev/euelections_dev2019.fr-de.tgt.de"),
+    ),
+    SubDataset(
+        name="newsdev2014",
+        target="en",
+        sources={"hi"},
+        url="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        path=("dev/newsdev2014.hi", "dev/newsdev2014.en"),
+    ),
+    SubDataset(
+        name="newsdev2015",
+        target="en",
+        sources={"fi"},
+        url="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        path=("dev/newsdev2015-fien-src.{src}.sgm", "dev/newsdev2015-fien-ref.en.sgm"),
+    ),
+    SubDataset(
+        name="newsdiscussdev2015",
+        target="en",
+        sources={"ro", "tr"},
+        url="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        path=("dev/newsdiscussdev2015-{src}en-src.{src}.sgm", "dev/newsdiscussdev2015-{src}en-ref.en.sgm"),
+    ),
+    SubDataset(
+        name="newsdev2016",
+        target="en",
+        sources={"ro", "tr"},
+        url="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        path=("dev/newsdev2016-{src}en-src.{src}.sgm", "dev/newsdev2016-{src}en-ref.en.sgm"),
+    ),
+    SubDataset(
+        name="newsdev2017",
+        target="en",
+        sources={"lv", "zh"},
+        url="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        path=("dev/newsdev2017-{src}en-src.{src}.sgm", "dev/newsdev2017-{src}en-ref.en.sgm"),
+    ),
+    SubDataset(
+        name="newsdev2018",
+        target="en",
+        sources={"et"},
+        url="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        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="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        path=("dev/newsdev2019-{src}en-src.{src}.sgm", "dev/newsdev2019-{src}en-ref.en.sgm"),
+    ),
+    SubDataset(
+        name="newsdiscussdev2015",
+        target="en",
+        sources={"fr"},
+        url="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        path=("dev/newsdiscussdev2015-{src}en-src.{src}.sgm", "dev/newsdiscussdev2015-{src}en-ref.en.sgm"),
+    ),
+    SubDataset(
+        name="newsdiscusstest2015",
+        target="en",
+        sources={"fr"},
+        url="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        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="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        path=("dev/newssyscomb2009.{src}", "dev/newssyscomb2009.en"),
+    ),
+    SubDataset(
+        name="newstest2008",
+        target="en",
+        sources={"cs", "de", "es", "fr", "hu"},
+        url="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        path=("dev/news-test2008.{src}", "dev/news-test2008.en"),
+    ),
+    SubDataset(
+        name="newstest2009",
+        target="en",
+        sources={"cs", "de", "es", "fr"},
+        url="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        path=("dev/newstest2009.{src}", "dev/newstest2009.en"),
+    ),
+    SubDataset(
+        name="newstest2010",
+        target="en",
+        sources={"cs", "de", "es", "fr"},
+        url="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        path=("dev/newstest2010.{src}", "dev/newstest2010.en"),
+    ),
+    SubDataset(
+        name="newstest2011",
+        target="en",
+        sources={"cs", "de", "es", "fr"},
+        url="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        path=("dev/newstest2011.{src}", "dev/newstest2011.en"),
+    ),
+    SubDataset(
+        name="newstest2012",
+        target="en",
+        sources={"cs", "de", "es", "fr", "ru"},
+        url="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        path=("dev/newstest2012.{src}", "dev/newstest2012.en"),
+    ),
+    SubDataset(
+        name="newstest2013",
+        target="en",
+        sources={"cs", "de", "es", "fr", "ru"},
+        url="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        path=("dev/newstest2013.{src}", "dev/newstest2013.en"),
+    ),
+    SubDataset(
+        name="newstest2014",
+        target="en",
+        sources={"cs", "de", "es", "fr", "hi", "ru"},
+        url="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        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="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        path=("dev/newstest2015-{src}en-src.{src}.sgm", "dev/newstest2015-{src}en-ref.en.sgm"),
+    ),
+    SubDataset(
+        name="newsdiscusstest2015",
+        target="en",
+        sources={"fr"},
+        url="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        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="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        path=("dev/newstest2016-{src}en-src.{src}.sgm", "dev/newstest2016-{src}en-ref.en.sgm"),
+    ),
+    SubDataset(
+        name="newstestB2016",
+        target="en",
+        sources={"fi"},
+        url="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        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="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        path=("dev/newstest2017-{src}en-src.{src}.sgm", "dev/newstest2017-{src}en-ref.en.sgm"),
+    ),
+    SubDataset(
+        name="newstestB2017",
+        target="en",
+        sources={"fi"},
+        url="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        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="http://data.statmt.org/wmt19/translation-task/dev.tgz",
+        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(
+                "The dataset for {}-en is currently not fully supported.".format(language_pair[1])
+            )
+        # +++++++++++++++++++++
+
+
+class Wmt(ABC, datasets.GeneratorBasedBuilder):
+    """WMT translation dataset."""
+
+    def __init__(self, *args, **kwargs):
+        if type(self) == Wmt and "config" not in kwargs:  # pylint: disable=unidiomatic-typecheck
+            raise ValueError(
+                "The raw `wmt_translate` can only be instantiated with the config "
+                "kwargs. You may want to use one of the `wmtYY_translate` "
+                "implementation instead to get the WMT dataset for a specific year."
+            )
+        super(Wmt, self).__init__(*args, **kwargs)
+
+    @property
+    @abstractmethod
+    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 = {}
+        for split, ss_names in self._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:
+                    logging.info("Skipping sub-dataset that does not include language pair: %s", ss_name)
+                else:
+                    filtered_subsets[split].append(ss_name)
+        logging.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
+                # +++++++++++++++++++++
+                logging.info("Skipping {} for now. Incomplete dataset for {}".format(dataset.name, 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
+                ), "For {0}, you must manually download the following file(s) from {1} and place them in {2}: {3}".format(
+                    dataset.name, dataset.get_url(source), 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)
+            ]
+
+        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):
+                logging.info("Skipping {} for now. Incomplete dataset for {}".format(dataset.name, self.config.name))
+                continue
+            # +++++++++++++++++++++
+
+            logging.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)
+
+            if ss_name.startswith("czeng"):
+                if ss_name.endswith("16pre"):
+                    sub_generator = functools.partial(_parse_tsv, language_pair=("en", "cs"))
+                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
+            elif len(files) == 1:
+                fname = files[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
+                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)
+                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(*files):
+                if not all(ex.values()):
+                    continue
+                # TODO(adarob): Add subset feature.
+                # ex["subset"] = subset
+                key = "{}/{}".format(ss_name, sub_key)
+                if with_translation is True:
+                    ex = {"translation": ex}
+                yield key, ex
+
+
+def _parse_parallel_sentences(f1, f2):
+    """Returns examples from parallel SGML or text files, which may be gzipped."""
+
+    def _parse_text(path):
+        """Returns the sentences from a single text file, which may be gzipped."""
+        split_path = path.split(".")
+
+        if split_path[-1] == "gz":
+            lang = split_path[-2]
+            with open(path, "rb") as f, gzip.GzipFile(fileobj=f) as g:
+                return g.read().decode("utf-8").split("\n"), lang
+
+        if split_path[-1] == "txt":
+            # CWMT
+            lang = split_path[-2].split("_")[-1]
+            lang = "zh" if lang in ("ch", "cn") else lang
+        else:
+            lang = split_path[-1]
+        with open(path, "rb") as f:
+            return f.read().decode("utf-8").split("\n"), lang
+
+    def _parse_sgm(path):
+        """Returns sentences from a single SGML file."""
+        lang = path.split(".")[-2]
+        sentences = []
+        # 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>")
+        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
+                    sentences.append(seg_match.groups()[0])
+        return sentences, lang
+
+    parse_file = _parse_sgm if 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)
+        l2_sentences, l2 = parse_file(f2_i)
+
+        assert len(l1_sentences) == len(l2_sentences), "Sizes do not match: %d vs %d for %s vs %s." % (
+            len(l1_sentences),
+            len(l2_sentences),
+            f1_i,
+            f2_i,
+        )
+
+        for line_id, (s1, s2) in enumerate(zip(l1_sentences, l2_sentences)):
+            key = "{}/{}".format(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 f:
+        fr_sentences = f.read().split("\n")
+    with open(de_path, encoding="utf-8") as f:
+        de_sentences = f.read().split("\n")
+    assert len(fr_sentences) == len(de_sentences), "Sizes do not match: %d vs %d for %s vs %s." % (
+        len(fr_sentences),
+        len(de_sentences),
+        fr_path,
+        de_path,
+    )
+    for line_id, (s1, s2) in enumerate(zip(fr_sentences, de_sentences)):
+        yield line_id, {"fr": s1, "de": s2}
+
+
+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:
+        if six.PY3:
+            # Workaround due to: https://github.com/tensorflow/tensorflow/issues/33563
+            utf_f = codecs.getreader("utf-8")(f)
+        else:
+            utf_f = 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, 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", path)
+        assert lang_match is not None, "Invalid TSV filename: %s" % path
+        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:
+                logging.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()}
+        logging.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 = "{}/{}".format(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:
+                logging.warning("Skipping invalid HindEnCorp line: %s", line)
+                continue
+            yield line_id, {"translation": {"en": split_line[3].strip(), "hi": split_line[4].strip()}}