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
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+*.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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+{"neen": {"description": "Evaluation datasets for low-resource machine translation: Nepali-English and Sinhala-English.\n", "citation": "@misc{guzmn2019new,\n    title={Two New Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-English},\n    author={Francisco Guzman and Peng-Jen Chen and Myle Ott and Juan Pino and Guillaume Lample and Philipp Koehn and Vishrav Chaudhary and Marc'Aurelio Ranzato},\n    year={2019},\n    eprint={1902.01382},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://github.com/facebookresearch/flores/", "license": "", "features": {"translation": {"languages": ["ne", "en"], "id": null, "_type": "Translation"}}, "supervised_keys": {"input": "ne", "output": "en"}, "builder_name": "flores", "config_name": "neen", "version": {"version_str": "1.1.0", "description": "", "datasets_version_to_prepare": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 1000483, "num_examples": 2836, "dataset_name": "flores"}, "validation": {"name": "validation", "num_bytes": 850660, "num_examples": 2560, "dataset_name": "flores"}}, "download_checksums": {"https://github.com/facebookresearch/flores/raw/master/data/wikipedia_en_ne_si_test_sets.tgz": {"num_bytes": 1542781, "checksum": "7a0245bb29fd03b46a1129831c183dfba0efc8452a9739d962759f25141aa648"}}, "download_size": 1542781, "dataset_size": 1851143, "size_in_bytes": 3393924}, "sien": {"description": "Evaluation datasets for low-resource machine translation: Nepali-English and Sinhala-English.\n", "citation": "@misc{guzmn2019new,\n    title={Two New Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-English},\n    author={Francisco Guzman and Peng-Jen Chen and Myle Ott and Juan Pino and Guillaume Lample and Philipp Koehn and Vishrav Chaudhary and Marc'Aurelio Ranzato},\n    year={2019},\n    eprint={1902.01382},\n    archivePrefix={arXiv},\n    primaryClass={cs.CL}\n}\n", "homepage": "https://github.com/facebookresearch/flores/", "license": "", "features": {"translation": {"languages": ["si", "en"], "id": null, "_type": "Translation"}}, "supervised_keys": {"input": "si", "output": "en"}, "builder_name": "flores", "config_name": "sien", "version": {"version_str": "1.1.0", "description": "", "datasets_version_to_prepare": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 984947, "num_examples": 2767, "dataset_name": "flores"}, "validation": {"name": "validation", "num_bytes": 1032610, "num_examples": 2899, "dataset_name": "flores"}}, "download_checksums": {"https://github.com/facebookresearch/flores/raw/master/data/wikipedia_en_ne_si_test_sets.tgz": {"num_bytes": 1542781, "checksum": "7a0245bb29fd03b46a1129831c183dfba0efc8452a9739d962759f25141aa648"}}, "download_size": 1542781, "dataset_size": 2017557, "size_in_bytes": 3560338}}

dummy/neen/1.1.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b082518357e95e2b1cea911b02a8760e99f9018367c49ec24095077b29344a9e
+size 1718

dummy/sien/1.1.0/dummy_data-zip-extracted/dummy_data/wikipedia_en_ne_si_test_sets/wikipedia.dev.si-en.en

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+This is the wrong translation!

dummy/sien/1.1.0/dummy_data-zip-extracted/dummy_data/wikipedia_en_ne_si_test_sets/wikipedia.dev.si-en.si

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+එවැනි ආවරණයක් ලබාදීමට රක්ෂණ සපයන්නෙකු කැමති වුවත් ඒ සාමාන් යයෙන් බොහෝ රටවල පොදු ප් රතිපත්තියට විරුද්ධය.

dummy/sien/1.1.0/dummy_data-zip-extracted/dummy_data/wikipedia_en_ne_si_test_sets/wikipedia.devtest.si-en.en

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+This is the wrong translation!

dummy/sien/1.1.0/dummy_data-zip-extracted/dummy_data/wikipedia_en_ne_si_test_sets/wikipedia.devtest.si-en.si

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+එවැනි ආවරණයක් ලබාදීමට රක්ෂණ සපයන්නෙකු කැමති වුවත් ඒ සාමාන් යයෙන් බොහෝ රටවල පොදු ප් රතිපත්තියට විරුද්ධය.

dummy/sien/1.1.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d022fff4af79488c93f480c11a4dc1744fb1450bd29884cf32d9e18aa164e7a8
+size 1772

flores.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
+"""Facebook Low Resource (FLoRes) machine translation benchmark dataset."""
+
+from __future__ import absolute_import, division, print_function
+
+import collections
+
+import datasets
+
+
+_DESCRIPTION = """\
+Evaluation datasets for low-resource machine translation: Nepali-English and Sinhala-English.
+"""
+
+_CITATION = """\
+@misc{guzmn2019new,
+    title={Two New Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-English},
+    author={Francisco Guzman and Peng-Jen Chen and Myle Ott and Juan Pino and Guillaume Lample and Philipp Koehn and Vishrav Chaudhary and Marc'Aurelio Ranzato},
+    year={2019},
+    eprint={1902.01382},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+"""
+
+_DATA_URL = "https://github.com/facebookresearch/flores/raw/master/data/wikipedia_en_ne_si_test_sets.tgz"
+
+# Tuple that describes a single pair of files with matching translations.
+# language_to_file is the map from language (2 letter string: example 'en')
+# to the file path in the extracted directory.
+TranslateData = collections.namedtuple("TranslateData", ["url", "language_to_file"])
+
+
+class FloresConfig(datasets.BuilderConfig):
+    """BuilderConfig for FLoRes."""
+
+    def __init__(self, language_pair=(None, None), **kwargs):
+        """BuilderConfig for FLoRes.
+
+        Args:
+            for the `datasets.features.text.TextEncoder` used for the features feature.
+          language_pair: pair of languages that will be used for translation. Should
+            contain 2-letter coded strings. First will be used at source and second
+            as target in supervised mode. For example: ("se", "en").
+          **kwargs: keyword arguments forwarded to super.
+        """
+        name = "%s%s" % (language_pair[0], language_pair[1])
+
+        description = ("Translation dataset from %s to %s") % (language_pair[0], language_pair[1])
+        super(FloresConfig, self).__init__(
+            name=name,
+            description=description,
+            version=datasets.Version("1.1.0", ""),
+            **kwargs,
+        )
+
+        # Validate language pair.
+        assert "en" in language_pair, ("Config language pair must contain `en`, got: %s", language_pair)
+        source, target = language_pair
+        non_en = source if target == "en" else target
+        assert non_en in ["ne", "si"], ("Invalid non-en language in pair: %s", non_en)
+
+        self.language_pair = language_pair
+
+
+class Flores(datasets.GeneratorBasedBuilder):
+    """FLoRes machine translation dataset."""
+
+    BUILDER_CONFIGS = [
+        FloresConfig(
+            language_pair=("ne", "en"),
+        ),
+        FloresConfig(
+            language_pair=("si", "en"),
+        ),
+    ]
+
+    def _info(self):
+        source, target = self.config.language_pair
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {"translation": datasets.features.Translation(languages=self.config.language_pair)}
+            ),
+            supervised_keys=(source, target),
+            homepage="https://github.com/facebookresearch/flores/",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        dl_dir = dl_manager.download_and_extract(_DATA_URL)
+
+        source, target = self.config.language_pair
+        non_en = source if target == "en" else target
+        path_tmpl = "{dl_dir}/wikipedia_en_ne_si_test_sets/wikipedia.{split}.{non_en}-en." "{lang}"
+
+        files = {}
+        for split in ("dev", "devtest"):
+            files[split] = {
+                "source_file": path_tmpl.format(dl_dir=dl_dir, split=split, non_en=non_en, lang=source),
+                "target_file": path_tmpl.format(dl_dir=dl_dir, split=split, non_en=non_en, lang=target),
+            }
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs=files["dev"]),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs=files["devtest"]),
+        ]
+
+    def _generate_examples(self, source_file, target_file):
+        """This function returns the examples in the raw (text) form."""
+        with open(source_file, encoding="utf-8") as f:
+            source_sentences = f.read().split("\n")
+        with open(target_file, encoding="utf-8") as f:
+            target_sentences = f.read().split("\n")
+
+        assert len(target_sentences) == len(source_sentences), "Sizes do not match: %d vs %d for %s vs %s." % (
+            len(source_sentences),
+            len(target_sentences),
+            source_file,
+            target_file,
+        )
+
+        source, target = self.config.language_pair
+        for idx, (l1, l2) in enumerate(zip(source_sentences, target_sentences)):
+            result = {"translation": {source: l1, target: l2}}
+            # Make sure that both translations are non-empty.
+            if all(result.values()):
+                yield idx, result