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:
+- tr
+licenses:
+- unknown
+multilinguality:
+- monolingual
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+task_categories:
+- text_classification
+task_ids:
+- sentiment-classification
+- sentiment-scoring
+---
+
+# Dataset Card for TurkishMovieSentiment: This dataset contains turkish movie 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)
+  - [Discussion of Social Impact and Biases](#discussion-of-social-impact-and-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://www.kaggle.com/mustfkeskin/turkish-movie-sentiment-analysis-dataset/tasks](https://www.kaggle.com/mustfkeskin/turkish-movie-sentiment-analysis-dataset/tasks)
+- **Point of Contact:** [Mustafa Keskin](https://www.linkedin.com/in/mustfkeskin/)
+
+### Dataset Summary
+
+This data set is a dataset from kaggle consisting of Turkish movie reviews and scored between 0-5.
+
+### Languages
+
+The dataset is based on Turkish.
+
+## Dataset Structure
+
+### Data Instances
+
+**Example 1:**
+
+**Comment:** Jean Reno denince zaten leon filmi gelir akla izlemeyen kalmamıştır ama kaldıysada ee ne duruyorsun hemen izle :),
+
+**Film_name:** Sevginin Gücü,
+
+**Point:** 5,0
+
+**Example 2:**
+
+**Comment:** Bence güzel bi film olmush.İzlenmeli.İnsana şükretmek gerektini hatırlatıyor.Ama cok da poh pohlanacak bi sey yapmamıslar,
+
+**Film_name:** Cinderella Man,
+
+**Point:** 2,5
+
+### Data Fields
+
+- **comment**(string) : Contatins turkish movie review
+- **film_name**(string) : Film name in Turkish.
+- **point**(float) : [0-5] floating point
+
+### Data Splits
+
+It is not divided into Train set and Test set.
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+[More Information Needed]
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+The dataset does not contain any additional 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
+
+### Discussion of Social Impact and Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+The dataset was created by [Mustafa Keskin](https://www.linkedin.com/in/mustfkeskin/).  
+
+### Licensing Information
+
+The data is under the [CC0: Public Domain](https://creativecommons.org/publicdomain/zero/1.0/)
+
+### Citation Information
+
+[More Information Needed]

dataset_infos.json

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+{"default": {"description": "This data set is a dataset from kaggle consisting of Turkish movie reviews and scored between 0-5.\n", "citation": "", "homepage": "https://www.kaggle.com/mustfkeskin/turkish-movie-sentiment-analysis-dataset", "license": "CC0: Public Domain", "features": {"point": {"dtype": "float32", "id": null, "_type": "Value"}, "comment": {"dtype": "string", "id": null, "_type": "Value"}, "film_name": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "turkish_movie_sentiment", "config_name": "default", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 33954560, "num_examples": 83227, "dataset_name": "turkish_movie_sentiment"}}, "download_checksums": {}, "download_size": 0, "post_processing_size": null, "dataset_size": 33954560, "size_in_bytes": 33954560}}

dummy/turkishmoviesentiment/1.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:cc5ed38f57f22cc6facf0fad1ea0c30846a422cb006d499f4001a7c7051c6301
+size 3034

turkish_movie_sentiment.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.
+# Lint as: python3
+"""TurkishMovieSentiment: This dataset contains turkish movie reviews."""
+
+from __future__ import absolute_import, division, print_function
+
+import csv
+import logging
+import os
+
+import datasets
+
+
+_DESCRIPTION = """\
+This data set is a dataset from kaggle consisting of Turkish movie reviews and scored between 0-5.
+"""
+
+_CITATION = ""
+_LICENSE = "CC0: Public Domain"
+_HOMEPAGE = "https://www.kaggle.com/mustfkeskin/turkish-movie-sentiment-analysis-dataset"
+_FILENAME = "turkish_movie_sentiment_dataset.csv"
+
+
+class TurkishMovieSentimentConfig(datasets.BuilderConfig):
+    """BuilderConfig for TurkishMovieSentiment"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for TurkishMovieSentiment.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(TurkishMovieSentimentConfig, self).__init__(**kwargs)
+
+
+class TurkishMovieSentiment(datasets.GeneratorBasedBuilder):
+    """TurkishMovieSentiment: This dataset contains turkish movie reviews."""
+
+    BUILDER_CONFIGS = [
+        TurkishMovieSentimentConfig(
+            name="turkishmoviesentiment",
+            version=datasets.Version("1.0.0"),
+            description="This dataset contains turkish movie reviews.",
+        ),
+    ]
+
+    @property
+    def manual_download_instructions(self):
+        return """\
+    You need to go to https://www.kaggle.com/mustfkeskin/turkish-movie-sentiment-analysis-dataset,
+    and manually download the TurkishMovieSentiment. Once it is completed,
+    a file named archive.zip will be appeared in your Downloads folder
+    or whichever folder your browser chooses to save files to. You then have
+    to unzip the file and move turkish_movie_sentiment_dataset.csv under <path/to/folder>.
+    The <path/to/folder> can e.g. be "~/manual_data".
+    TurkishMovieSentiment can then be loaded using the following command `datasets.load_dataset("turkishmoviesentiment", data_dir="<path/to/folder>")`.
+    """
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "point": datasets.Value("float32"),
+                    "comment": datasets.Value("string"),
+                    "film_name": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+            # Homepage of the dataset for documentation
+            homepage=_HOMEPAGE,
+            # License for the dataset if available
+            license=_LICENSE,
+            # Citation for the dataset
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        path_to_manual_file = os.path.abspath(os.path.expanduser(dl_manager.manual_dir))
+        if not os.path.exists(path_to_manual_file):
+            raise FileNotFoundError(
+                "{} does not exist. Make sure you insert a manual dir via `datasets.load_dataset('turkishmoviesentiment', data_dir=...)` that includes a file name {}. Manual download instructions: {})".format(
+                    path_to_manual_file, _FILENAME, self.manual_download_instructions
+                )
+            )
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(path_to_manual_file, _FILENAME)}
+            )
+        ]
+
+    def _generate_examples(self, filepath):
+        """Generate TurkishMovieSentiment examples."""
+        logging.info("⏳ Generating examples from = %s", filepath)
+        with open(filepath, encoding="utf-8") as f:
+            rdr = csv.reader(f, delimiter=",")
+            next(rdr)
+            rownum = 0
+            for row in rdr:
+                rownum += 1
+                yield rownum, {
+                    "comment": row[0],
+                    "film_name": row[1],
+                    "point": row[2].replace(",", "."),  # convert string to floating point ([0-5])
+                }