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:
+  - machine-generated
+languages:
+  - ur
+licenses:
+  - odbl-1-0
+multilinguality:
+  - monolingual
+size_categories:
+  - 10K<n<100K
+source_datasets:
+  - original
+task_categories:
+  - text-classification
+task_ids:
+  - sentiment-classification
+---
+
+# Dataset Card for ImDB Urdu Reviews
+
+## 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:** [Github](https://github.com/mirfan899/Urdu)
+- **Repository:** [Github](https://github.com/mirfan899/Urdu)
+- **Paper:** [Aclweb](http://www.aclweb.org/anthology/P11-1015)
+- **Leaderboard:**
+- **Point of Contact:** [Ikram Ali](https://github.com/akkefa)
+
+### Dataset Summary
+
+[More Information Needed]
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+[More Information Needed]
+
+### Data Fields
+
+- sentence: The movie review which was translated into Urdu.
+- sentiment: The sentiment exhibited in the review, either positive or negative.
+
+### 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
+
+[More Information Needed]

dataset_infos.json

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+{"default": {"description": "\nLarge Movie translated Urdu Reviews Dataset.\nThis is a dataset for binary sentiment classification containing substantially more data than previous\nbenchmark datasets. We provide a set of 40,000 highly polar movie reviews for training, and 10,000 for testing.\nTo increase the availability of sentiment analysis dataset for a low recourse language like Urdu,\nwe opted to use the already available IMDB Dataset. we have translated this dataset using google translator.\nThis is a binary classification dataset having two classes as positive and negative.\nThe reason behind using this dataset is high polarity for each class.\nIt contains 50k samples equally divided in two classes.\n", "citation": "\n@InProceedings{maas-EtAl:2011:ACL-HLT2011,\n  author    = {Maas, Andrew L. and Daly,nRaymond E. and Pham, Peter T. and Huang, Dan and Ng, Andrew Y...},\n  title     = {Learning Word Vectors for Sentiment Analysis},\n  month     = {June},\n  year      = {2011},\n  address   = {Portland, Oregon, USA},\n  publisher = {Association for Computational Linguistics},\n  pages     = {142--150},\n  url       = {http://www.aclweb.org/anthology/P11-1015}\n}\n", "homepage": "https://github.com/mirfan899/Urdu", "license": "", "features": {"sentence": {"dtype": "string", "id": null, "_type": "Value"}, "sentiment": {"num_classes": 2, "names": ["positive", "negative"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "imdb", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 114670811, "num_examples": 50000, "dataset_name": "imdb"}}, "download_checksums": {"https://github.com/mirfan899/Urdu/blob/master/sentiment/imdb_urdu_reviews.csv.tar.gz?raw=true": {"num_bytes": 31510992, "checksum": "f60f7e9972661dc5d8ec1c867972ae35f86dac32de43a274a2a794095dccdf99"}}, "download_size": 31510992, "post_processing_size": null, "dataset_size": 114670811, "size_in_bytes": 146181803}}

dummy/1.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:72e09af3bdf2910efa7e7ed2f9a8c699b52ac65da537da7c5f2edfe80b985790
+size 1649

imdb_urdu_reviews.py

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+"""IMDB Urdu movie reviews dataset."""
+
+from __future__ import absolute_import, division, print_function
+
+import csv
+import os
+
+import datasets
+
+
+_CITATION = """
+@InProceedings{maas-EtAl:2011:ACL-HLT2011,
+  author    = {Maas, Andrew L. and Daly,nRaymond E. and Pham, Peter T. and Huang, Dan and Ng, Andrew Y...},
+  title     = {Learning Word Vectors for Sentiment Analysis},
+  month     = {June},
+  year      = {2011},
+  address   = {Portland, Oregon, USA},
+  publisher = {Association for Computational Linguistics},
+  pages     = {142--150},
+  url       = {http://www.aclweb.org/anthology/P11-1015}
+}
+"""
+
+_DESCRIPTION = """
+Large Movie translated Urdu Reviews Dataset.
+This is a dataset for binary sentiment classification containing substantially more data than previous
+benchmark datasets. We provide a set of 40,000 highly polar movie reviews for training, and 10,000 for testing.
+To increase the availability of sentiment analysis dataset for a low recourse language like Urdu,
+we opted to use the already available IMDB Dataset. we have translated this dataset using google translator.
+This is a binary classification dataset having two classes as positive and negative.
+The reason behind using this dataset is high polarity for each class.
+It contains 50k samples equally divided in two classes.
+"""
+
+_URL = "https://github.com/mirfan899/Urdu/blob/master/sentiment/imdb_urdu_reviews.csv.tar.gz?raw=true"
+
+_HOMEPAGE = "https://github.com/mirfan899/Urdu"
+
+
+class ImdbUrduReviews(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "sentence": datasets.Value("string"),
+                    "sentiment": datasets.ClassLabel(names=["positive", "negative"]),
+                }
+            ),
+            citation=_CITATION,
+            homepage=_HOMEPAGE,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        dl_path = dl_manager.download_and_extract(_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(dl_path, "imdb_urdu_reviews.csv")}
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+        with open(filepath, encoding="utf-8") as f:
+            reader = csv.reader(f, delimiter=",")
+            for id_, row in enumerate(reader):
+                if id_ == 0:
+                    continue
+                yield id_, {"sentiment": row[1], "sentence": row[0]}