Update files from the datasets library (from 1.2.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

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README.md

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+---
+annotations_creators:
+- found
+language_creators:
+- found
+multilinguality:
+- multilingual
+languages:
+- en
+- vi
+licenses:
+- unknown
+size_categories:
+- 100K<n<1M
+source_datasets:
+- original
+task_categories:
+- conditional-text-generation
+task_ids:
+- machine-translation
+---
+
+# Dataset Card for mt_eng_vietnamese
+
+## Table of Contents
+- [Dataset Card for mt_eng_vietnamese](#dataset-card-for-mt_eng_vietnamese)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+    - [Annotations](#annotations)
+      - [Annotation process](#annotation-process)
+      - [Who are the annotators?](#who-are-the-annotators)
+    - [Personal and Sensitive Information](#personal-and-sensitive-information)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+  - [Additional Information](#additional-information)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** https://nlp.stanford.edu/projects/nmt/data/iwslt15.en-vi/
+- **Repository:** [Needs More Information]
+- **Paper:** [Needs More Information]
+- **Leaderboard:** [Needs More Information]
+- **Point of Contact:** [Needs More Information]
+
+### Dataset Summary
+
+Preprocessed Dataset from IWSLT'15 English-Vietnamese machine translation: English-Vietnamese.
+
+### Supported Tasks and Leaderboards
+
+Machine Translation 
+
+### Languages
+
+English, Vietnamese
+
+## Dataset Structure
+
+### Data Instances
+
+An example from the dataset:
+```
+{
+  'translation': {
+    'en': 'In 4 minutes , atmospheric chemist Rachel Pike provides a glimpse of the massive scientific effort behind the bold headlines on climate change , with her team -- one of thousands who contributed -- taking a risky flight over the rainforest in pursuit of data on a key molecule .', 
+    'vi': 'Trong 4 phút , chuyên gia hoá học khí quyển Rachel Pike giới thiệu sơ lược về những nỗ lực khoa học miệt mài đằng sau những tiêu đề táo bạo về biến đổi khí hậu , cùng với đoàn nghiên cứu của mình -- hàng ngàn người đã cống hiến cho dự án này -- một chuyến bay mạo hiểm qua rừng già để tìm kiếm thông tin về một phân tử then chốt .'
+    }
+}
+```
+
+
+### Data Fields
+
+- translation:
+  - en: text in english
+  - vi: text in vietnamese
+
+
+### Data Splits
+
+train: 133318, validation: 1269, test: 1269
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+```
+@inproceedings{Luong-Manning:iwslt15,
+        Address = {Da Nang, Vietnam}
+        Author = {Luong, Minh-Thang  and Manning, Christopher D.},
+        Booktitle = {International Workshop on Spoken Language Translation},
+        Title = {Stanford Neural Machine Translation Systems for Spoken Language Domain},
+        Year = {2015}}
+
+```

dataset_infos.json

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+{"iwslt2015-vi-en": {"description": "Preprocessed Dataset from IWSLT'15 English-Vietnamese machine translation: English-Vietnamese.\n", "citation": "@inproceedings{Luong-Manning:iwslt15,\n        Address = {Da Nang, Vietnam}\n        Author = {Luong, Minh-Thang  and Manning, Christopher D.},\n        Booktitle = {International Workshop on Spoken Language Translation},\n        Title = {Stanford Neural Machine Translation Systems for Spoken Language Domain},\n        Year = {2015}}\n", "homepage": "https://nlp.stanford.edu/projects/nmt/data/iwslt15.en-vi/", "license": "", "features": {"translation": {"languages": ["vi", "en"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": {"input": "vi", "output": "en"}, "builder_name": "mt_eng_vietnamese", "config_name": "iwslt2015-vi-en", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 32478282, "num_examples": 133318, "dataset_name": "mt_eng_vietnamese"}, "validation": {"name": "validation", "num_bytes": 323743, "num_examples": 1269, "dataset_name": "mt_eng_vietnamese"}, "test": {"name": "test", "num_bytes": 323743, "num_examples": 1269, "dataset_name": "mt_eng_vietnamese"}}, "download_checksums": {"https://nlp.stanford.edu/projects/nmt/data/iwslt15.en-vi/train.vi": {"num_bytes": 18074646, "checksum": "707206edf2dc0280273952c7b70544ea8a1363aa69aaeb9d70514b888dc3067d"}, "https://nlp.stanford.edu/projects/nmt/data/iwslt15.en-vi/train.en": {"num_bytes": 13603614, "checksum": "c26dfeed74b6bf3752f5ca552f2412456f0de153f7c804df8717931fb3a5c78a"}, "https://nlp.stanford.edu/projects/nmt/data/iwslt15.en-vi/tst2012.vi": {"num_bytes": 188396, "checksum": "01004078b3f36b0c46e81b65fc6851230b3c823405c76d1d82ef3b786b512ff0"}, "https://nlp.stanford.edu/projects/nmt/data/iwslt15.en-vi/tst2012.en": {"num_bytes": 140250, "checksum": "b8fbcd0d4199d41276421d1f7228298df67dd9e2c5c134c2ee8cdf3ec27801e2"}, "https://nlp.stanford.edu/projects/nmt/data/iwslt15.en-vi/tst2013.vi": {"num_bytes": 183855, "checksum": "29af16842808da2812b8fd4d47fc05d082ba870e60ab7755090ad04b380994cd"}, "https://nlp.stanford.edu/projects/nmt/data/iwslt15.en-vi/tst2013.en": {"num_bytes": 132264, "checksum": "3860ce60bc5b85d96cc2d3d580cf1bc9d62440e939c1b964676d3607c4e8f1df"}}, "download_size": 32323025, "post_processing_size": null, "dataset_size": 33125768, "size_in_bytes": 65448793}, "iwslt2015-en-vi": {"description": "Preprocessed Dataset from IWSLT'15 English-Vietnamese machine translation: English-Vietnamese.\n", "citation": "@inproceedings{Luong-Manning:iwslt15,\n        Address = {Da Nang, Vietnam}\n        Author = {Luong, Minh-Thang  and Manning, Christopher D.},\n        Booktitle = {International Workshop on Spoken Language Translation},\n        Title = {Stanford Neural Machine Translation Systems for Spoken Language Domain},\n        Year = {2015}}\n", "homepage": "https://nlp.stanford.edu/projects/nmt/data/iwslt15.en-vi/", "license": "", "features": {"translation": {"languages": ["en", "vi"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": {"input": "en", "output": "vi"}, "builder_name": "mt_eng_vietnamese", "config_name": "iwslt2015-en-vi", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 32478282, "num_examples": 133318, "dataset_name": "mt_eng_vietnamese"}, "validation": {"name": "validation", "num_bytes": 323743, "num_examples": 1269, "dataset_name": "mt_eng_vietnamese"}, "test": {"name": "test", "num_bytes": 323743, "num_examples": 1269, "dataset_name": "mt_eng_vietnamese"}}, "download_checksums": {"https://nlp.stanford.edu/projects/nmt/data/iwslt15.en-vi/train.en": {"num_bytes": 13603614, "checksum": "c26dfeed74b6bf3752f5ca552f2412456f0de153f7c804df8717931fb3a5c78a"}, "https://nlp.stanford.edu/projects/nmt/data/iwslt15.en-vi/train.vi": {"num_bytes": 18074646, "checksum": "707206edf2dc0280273952c7b70544ea8a1363aa69aaeb9d70514b888dc3067d"}, "https://nlp.stanford.edu/projects/nmt/data/iwslt15.en-vi/tst2012.en": {"num_bytes": 140250, "checksum": "b8fbcd0d4199d41276421d1f7228298df67dd9e2c5c134c2ee8cdf3ec27801e2"}, "https://nlp.stanford.edu/projects/nmt/data/iwslt15.en-vi/tst2012.vi": {"num_bytes": 188396, "checksum": "01004078b3f36b0c46e81b65fc6851230b3c823405c76d1d82ef3b786b512ff0"}, "https://nlp.stanford.edu/projects/nmt/data/iwslt15.en-vi/tst2013.en": {"num_bytes": 132264, "checksum": "3860ce60bc5b85d96cc2d3d580cf1bc9d62440e939c1b964676d3607c4e8f1df"}, "https://nlp.stanford.edu/projects/nmt/data/iwslt15.en-vi/tst2013.vi": {"num_bytes": 183855, "checksum": "29af16842808da2812b8fd4d47fc05d082ba870e60ab7755090ad04b380994cd"}}, "download_size": 32323025, "post_processing_size": null, "dataset_size": 33125768, "size_in_bytes": 65448793}}

dummy/iwslt2015-en-vi/1.0.0/dummy_data.zip

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dummy/iwslt2015-vi-en/1.0.0/dummy_data.zip

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mt_eng_vietnamese.py

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+# coding=utf-8
+# Copyright 2020 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.
+
+from __future__ import absolute_import, division, print_function
+
+import collections
+
+import datasets
+
+
+_DESCRIPTION = """\
+Preprocessed Dataset from IWSLT'15 English-Vietnamese machine translation: English-Vietnamese.
+"""
+
+_CITATION = """\
+@inproceedings{Luong-Manning:iwslt15,
+        Address = {Da Nang, Vietnam}
+        Author = {Luong, Minh-Thang  and Manning, Christopher D.},
+        Booktitle = {International Workshop on Spoken Language Translation},
+        Title = {Stanford Neural Machine Translation Systems for Spoken Language Domain},
+        Year = {2015}}
+"""
+
+_DATA_URL = "https://nlp.stanford.edu/projects/nmt/data/iwslt15.en-vi/{}.{}"
+
+# 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 MT_Eng_ViConfig(datasets.BuilderConfig):
+    """BuilderConfig for MT_Eng_Vietnamese."""
+
+    def __init__(self, language_pair=(None, None), **kwargs):
+        """BuilderConfig for MT_Eng_Vi.
+        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: ("vi", "en").
+          **kwargs: keyword arguments forwarded to super.
+        """
+
+        description = ("Translation dataset from %s to %s") % (language_pair[0], language_pair[1])
+        super(MT_Eng_ViConfig, self).__init__(
+            description=description,
+            version=datasets.Version("1.0.0"),
+            **kwargs,
+        )
+        self.language_pair = language_pair
+
+
+class MTEngVietnamese(datasets.GeneratorBasedBuilder):
+    """English Vietnamese machine translation dataset from IWSLT2015."""
+
+    BUILDER_CONFIGS = [
+        MT_Eng_ViConfig(
+            name="iwslt2015-vi-en",
+            language_pair=("vi", "en"),
+        ),
+        MT_Eng_ViConfig(
+            name="iwslt2015-en-vi",
+            language_pair=("en", "vi"),
+        ),
+    ]
+    BUILDER_CONFIG_CLASS = MT_Eng_ViConfig
+
+    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://nlp.stanford.edu/projects/nmt/data/iwslt15.en-vi/",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        source, target = self.config.language_pair
+
+        files = {}
+        for split in ("train", "dev", "test"):
+            if split == "dev":
+                dl_dir_src = dl_manager.download_and_extract(_DATA_URL.format("tst2012", source))
+                dl_dir_tar = dl_manager.download_and_extract(_DATA_URL.format("tst2012", target))
+            if split == "dev":
+                dl_dir_src = dl_manager.download_and_extract(_DATA_URL.format("tst2013", source))
+                dl_dir_tar = dl_manager.download_and_extract(_DATA_URL.format("tst2013", target))
+            if split == "train":
+                dl_dir_src = dl_manager.download_and_extract(_DATA_URL.format(split, source))
+                dl_dir_tar = dl_manager.download_and_extract(_DATA_URL.format(split, target))
+
+            files[split] = {"source_file": dl_dir_src, "target_file": dl_dir_tar}
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs=files["train"]),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs=files["dev"]),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs=files["test"]),
+        ]
+
+    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")
+
+        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.
+            yield idx, result