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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+# 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
+"""ParaCrawl (Bitextor) parallel open-source machine translation benchmark."""
+
+from __future__ import absolute_import, division, print_function
+
+import collections
+
+import datasets
+
+
+_DESCRIPTION = "Web-Scale Parallel Corpora for Official European Languages."
+
+_BENCHMARK_URL = "https://paracrawl.eu/releases.html"
+
+_CITATION = """\
+@misc {paracrawl,
+    title  = {ParaCrawl},
+    year   = {2018},
+    url    = {http://paracrawl.eu/download.html.}
+}
+"""
+
+_BASE_DATA_URL_FORMAT_STR = (
+    "https://s3.amazonaws.com/web-language-models/" "paracrawl/release4/en-{target_lang}.bicleaner07." "txt.gz"
+)
+
+
+def _target_languages():
+    """Create the sorted dictionary of language codes, and language names.
+
+    Returns:
+      The sorted dictionary as an instance of `collections.OrderedDict`.
+    """
+    langs = {
+        "bg": "Bulgarian",
+        "cs": "Czech",
+        "da": "Danish",
+        "de": "German",
+        "el": "Greek",
+        "es": "Spanish",
+        "et": "Estonian",
+        "fi": "Finnish",
+        "fr": "French",
+        "ga": "Irish",
+        "hr": "Croatian",
+        "hu": "Hungarian",
+        "it": "Italian",
+        "lt": "Lithuanian",
+        "lv": "Latvian",
+        "mt": "Maltese",
+        "nl": "Dutch",
+        "pl": "Polish",
+        "pt": "Portuguese",
+        "ro": "Romanian",
+        "sk": "Slovak",
+        "sl": "Slovenian",
+        "sv": "Swedish",
+    }
+    return collections.OrderedDict(sorted(langs.items()))
+
+
+class ParaCrawlConfig(datasets.BuilderConfig):
+    """BuilderConfig for ParaCrawl."""
+
+    def __init__(self, target_language=None, **kwargs):
+        """BuilderConfig for ParaCrawl.
+
+        Args:
+            for the `datasets.features.text.TextEncoder` used for the features feature.
+          target_language: Target language that will be used to translate to from
+            English which is always the source language. It has to contain 2-letter
+            coded strings. For example: "se", "hu".
+          **kwargs: Keyword arguments forwarded to super.
+        """
+        # Validate the target language.
+        if target_language not in _target_languages():
+            raise ValueError("Invalid target language: %s " % target_language)
+
+        # Initialize the base class.
+        name = "en%s" % (target_language)
+
+        description = ("Translation dataset from English to %s.") % (target_language)
+        super(ParaCrawlConfig, self).__init__(name=name, description=description, **kwargs)
+
+        # Store the attributes.
+
+        self.target_language = target_language
+        self.data_url = _BASE_DATA_URL_FORMAT_STR.format(target_lang=target_language)
+
+
+class ParaCrawl(datasets.GeneratorBasedBuilder):
+    """ParaCrawl machine translation dataset."""
+
+    # Version history:
+    # 1.0.0: S3 (new shuffling, sharding and slicing mechanism).
+    # 0.1.0: Initial version.
+    BUILDER_CONFIGS = [
+        # The version below does not refer to the version of the released
+        # database. It only indicates the version of the TFDS integration.
+        ParaCrawlConfig(  # pylint: disable=g-complex-comprehension
+            target_language=target_language,
+            version=datasets.Version("1.0.0"),
+        )
+        for target_language in _target_languages()
+    ]
+
+    def _info(self):
+        target_language = self.config.target_language
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {"translation": datasets.features.Translation(languages=("en", target_language))}
+            ),
+            supervised_keys=("en", target_language),
+            homepage=_BENCHMARK_URL,
+            citation=_CITATION,
+        )
+
+    def _vocab_text_gen(self, files, language):
+        for _, ex in self._generate_examples(**files):
+            yield ex[language]
+
+    def _split_generators(self, dl_manager):
+        # Download the data file.
+        data_file = dl_manager.download_and_extract({"data_file": self.config.data_url})
+
+        # Return the single split of the data.
+        return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs=data_file)]
+
+    def _generate_examples(self, data_file):
+        """This function returns the examples in the raw (text) form."""
+        target_language = self.config.target_language
+
+        with open(data_file, encoding="utf-8") as f:
+            for idx, line in enumerate(f):
+                line_parts = line.strip().split("\t")
+                if len(line_parts) != 2:
+                    msg = (
+                        "Wrong data format in line {}. The line '{}' does " "not have exactly one delimiter."
+                    ).format(idx, line)
+                    raise ValueError(msg)
+                source, target = line_parts[0].strip(), line_parts[1].strip()
+                yield idx, {"translation": {"en": source, target_language: target}}