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
+languages:
+- en
+- fa
+licenses:
+- unknown
+multilinguality:
+- translation
+size_categories:
+- 1k<10K
+source_datasets:
+- original
+task_categories:
+- conditional-text-generation
+task_ids:
+- machine-translation
+---
+
+# Dataset Card for [tep_en_fa_para]
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [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:**[TEP: Tehran English-Persian parallel corpus](http://opus.nlpl.eu/TEP.php)
+- **Repository:**
+- **Paper:**
+- **Leaderboard:**
+- **Point of Contact:**
+
+### Dataset Summary
+
+TEP: Tehran English-Persian parallel corpus. The first free Eng-Per corpus, provided by the Natural Language and Text Processing Laboratory, University of Tehran.
+
+### Supported Tasks and Leaderboards
+
+The underlying task is machine translation for language pair English-Persian
+
+### Languages
+
+English, Persian
+
+## Dataset Structure
+
+### Data Instances
+
+[More Information Needed]
+
+### Data Fields
+
+[More Information Needed]
+
+### Data Splits
+
+[More Information Needed]
+
+## 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
+M. T. Pilevar, H. Faili, and A. H. Pilevar, “TEP: Tehran English-Persian Parallel Corpus”, in proceedings of 12th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing-2011).

dataset_infos.json

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+{"en-fa": {"description": "TEP: Tehran English-Persian parallel corpus. The first free Eng-Per corpus, provided by the Natural Language and Text Processing Laboratory, University of Tehran.\n", "citation": "@InProceedings{\u201cTEP: Tehran English-Persian Parallel Corpus\u201d,\ntitle = {TEP: Tehran English-Persian Parallel Corpus\u201d, in proceedings of 12th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing-2011)},\nauthors={M. T. Pilevar, H. Faili, and A. H. Pilevar, },\nyear={2011}\n}\n", "homepage": "http://opus.nlpl.eu/TEP.php", "license": "", "features": {"translation": {"languages": ["en", "fa"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": null, "builder_name": "tep_en_fa_para", "config_name": "en-fa", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 58735557, "num_examples": 612087, "dataset_name": "tep_en_fa_para"}}, "download_checksums": {"https://object.pouta.csc.fi/OPUS-TEP/v1/moses/en-fa.txt.zip": {"num_bytes": 16353318, "checksum": "190690734392e1898aaee2e46093883c086de3e11e903ab3c07fac54e350a238"}}, "download_size": 16353318, "post_processing_size": null, "dataset_size": 58735557, "size_in_bytes": 75088875}}

dummy/en-fa/1.1.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ad9fa8ee734f22f609fda627b6bc5bd4b2c5d593736fb5c57d6ea22127fdbb7b
+size 792

tep_en_fa_para.py

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+# coding=utf-8
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# 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.
+"""TEP: Tehran English-Persian parallel corpus."""
+
+from __future__ import absolute_import, division, print_function
+
+import os
+
+import datasets
+
+
+_CITATION = """\
+@InProceedings{“TEP: Tehran English-Persian Parallel Corpus”,
+title = {TEP: Tehran English-Persian Parallel Corpus”, in proceedings of 12th International Conference \
+on Intelligent Text Processing and Computational Linguistics (CICLing-2011)},
+authors={M. T. Pilevar, H. Faili, and A. H. Pilevar, },
+year={2011}
+}
+"""
+
+
+_DESCRIPTION = """\
+TEP: Tehran English-Persian parallel corpus. The first free Eng-Per corpus, provided by the Natural Language and Text Processing Laboratory, University of Tehran.
+"""
+
+
+_HOMEPAGE = "http://opus.nlpl.eu/TEP.php"
+
+
+_LICENSE = ""
+
+
+_URLs = {"train": "https://object.pouta.csc.fi/OPUS-TEP/v1/moses/en-fa.txt.zip"}
+
+
+class TepEnFaPara(datasets.GeneratorBasedBuilder):
+    """TEP: Tehran English-Persian parallel corpus."""
+
+    VERSION = datasets.Version("1.1.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="en-fa", version=VERSION),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {"translation": datasets.features.Translation(languages=tuple(self.config.name.split("-")))}
+            ),
+            supervised_keys=None,
+            homepage="http://opus.nlpl.eu/TEP.php",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        data_dir = dl_manager.download_and_extract(_URLs)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "source_file": os.path.join(data_dir["train"], "TEP.en-fa.en"),
+                    "target_file": os.path.join(data_dir["train"], "TEP.en-fa.fa"),
+                    "split": "train",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, source_file, target_file, split):
+        """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 = tuple(self.config.name.split("-"))
+        for idx, (l1, l2) in enumerate(zip(source_sentences, target_sentences)):
+            result = {"translation": {source: l1, target: l2}}
+            yield idx, result