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:
+- ar
+licenses:
+- unknown
+multilinguality:
+- monolingual
+size_categories:
+- 10k<n<100k
+source_datasets:
+- original
+task_categories:
+- text-classification
+task_ids:
+- multi-class-classification
+---
+
+# Dataset Card for Hard
+
+## 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:** [Hard](https://github.com/elnagara/HARD-Arabic-Dataset)
+- **Repository:** [Hard](https://github.com/elnagara/HARD-Arabic-Dataset)
+- **Paper:** [Hotel Arabic-Reviews Dataset Construction for Sentiment Analysis Applications](https://link.springer.com/chapter/10.1007/978-3-319-67056-0_3)
+- **Point of Contact:** [Ashraf Elnagar](ashraf@sharjah.ac.ae)
+
+### Dataset Summary
+
+This dataset contains 93,700 hotel reviews in Arabic language.The hotel reviews were collected from Booking.com website during June/July 2016.The reviews are expressed in Modern Standard Arabic as well as dialectal Arabic.The following table summarize some tatistics on the HARD Dataset.
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+The dataset is based on Arabic.
+
+## Dataset Structure
+
+### Data Instances
+
+A typical data point comprises a rating from 1 to 5 for hotels.  
+
+### Data Fields
+
+[More Information Needed]
+
+### Data Splits
+
+The dataset is not split.
+
+## 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

dataset_infos.json

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+{"plain_text": {"description": "This dataset contains 93700 hotel reviews in Arabic language.The hotel reviews were collected from Booking.com website during June/July 2016.The reviews are expressed in Modern Standard Arabic as well as dialectal Arabic.The following table summarize some tatistics on the HARD Dataset.\n", "citation": "@incollection{elnagar2018hotel,\n  title={Hotel Arabic-reviews dataset construction for sentiment analysis applications},\n  author={Elnagar, Ashraf and Khalifa, Yasmin S and Einea, Anas},\n  booktitle={Intelligent Natural Language Processing: Trends and Applications},\n  pages={35--52},\n  year={2018},\n  publisher={Springer}\n}\n", "homepage": "https://github.com/elnagara/HARD-Arabic-Dataset", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 5, "names": ["1", "2", "3", "4", "5"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "hard", "config_name": "plain_text", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 27507085, "num_examples": 105698, "dataset_name": "hard"}}, "download_checksums": {"https://raw.githubusercontent.com/elnagara/HARD-Arabic-Dataset/master/data/balanced-reviews.zip": {"num_bytes": 8508677, "checksum": "1939c1ca59ff50bd3887223b153c7fb5c9fd232b405320244c55791bc8b5d448"}}, "download_size": 8508677, "post_processing_size": null, "dataset_size": 27507085, "size_in_bytes": 36015762}}

dummy/plain_text/1.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f3db1abfa2e9cc8a6bfb3c5598a2a8138c6c6dca8a6c4c2ea406b23bf3b3194a
+size 556

hard.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
+"""Hotel Reviews in Arabic language"""
+
+from __future__ import absolute_import, division, print_function
+
+import os
+
+import datasets
+
+
+_DESCRIPTION = """\
+This dataset contains 93700 hotel reviews in Arabic language.\
+The hotel reviews were collected from Booking.com website during June/July 2016.\
+The reviews are expressed in Modern Standard Arabic as well as dialectal Arabic.\
+The following table summarize some tatistics on the HARD Dataset.
+"""
+
+_CITATION = """\
+@incollection{elnagar2018hotel,
+  title={Hotel Arabic-reviews dataset construction for sentiment analysis applications},
+  author={Elnagar, Ashraf and Khalifa, Yasmin S and Einea, Anas},
+  booktitle={Intelligent Natural Language Processing: Trends and Applications},
+  pages={35--52},
+  year={2018},
+  publisher={Springer}
+}
+"""
+
+_DOWNLOAD_URL = "https://raw.githubusercontent.com/elnagara/HARD-Arabic-Dataset/master/data/balanced-reviews.zip"
+
+
+class HardConfig(datasets.BuilderConfig):
+    """BuilderConfig for Hard."""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for Hard.
+
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(HardConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
+
+
+class Hard(datasets.GeneratorBasedBuilder):
+    """Hard dataset."""
+
+    BUILDER_CONFIGS = [
+        HardConfig(
+            name="plain_text",
+            description="Plain text",
+        )
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "text": datasets.Value("string"),
+                    "label": datasets.features.ClassLabel(
+                        names=[
+                            "1",
+                            "2",
+                            "3",
+                            "4",
+                            "5",
+                        ]
+                    ),
+                }
+            ),
+            supervised_keys=None,
+            homepage="https://github.com/elnagara/HARD-Arabic-Dataset",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        data_dir = dl_manager.download_and_extract(_DOWNLOAD_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={"directory": os.path.join(data_dir, "balanced-reviews.txt")}
+            ),
+        ]
+
+    def _generate_examples(self, directory):
+        """Generate examples."""
+        with open(directory, mode="r", encoding="utf-16") as file:
+            for id_, line in enumerate(file.read().splitlines()[1:]):
+                _, _, rating, _, _, _, review_text = line.split("\t")
+                yield str(id_), {"text": review_text, "label": rating}