Delete loading script

emotone_ar.py

@@ -1,79 +0,0 @@
-# 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.
-"""Dataset of 10065 tweets in Arabic for Emotion detection in Arabic text """
-
-
-import csv
-
-import datasets
-from datasets.tasks import TextClassification
-
-
-_CITATION = """\
-@inbook{inbook,
-author = {Al-Khatib, Amr and El-Beltagy, Samhaa},
-year = {2018},
-month = {01},
-pages = {105-114},
-title = {Emotional Tone Detection in Arabic Tweets: 18th International Conference, CICLing 2017, Budapest, Hungary, April 17–23, 2017, Revised Selected Papers, Part II},
-isbn = {978-3-319-77115-1},
-doi = {10.1007/978-3-319-77116-8_8}
-}
-"""
-
-
-_DESCRIPTION = """\
-Dataset of 10065 tweets in Arabic for Emotion detection in Arabic text"""
-
-
-_HOMEPAGE = "https://github.com/AmrMehasseb/Emotional-Tone"
-
-
-_DOWNLOAD_URL = "https://raw.githubusercontent.com/AmrMehasseb/Emotional-Tone/master/Emotional-Tone-Dataset.csv"
-
-
-class EmotoneAr(datasets.GeneratorBasedBuilder):
-    """Dataset of 10065 tweets in Arabic for Emotions detection in Arabic text"""
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "tweet": datasets.Value("string"),
-                    "label": datasets.features.ClassLabel(
-                        names=["none", "anger", "joy", "sadness", "love", "sympathy", "surprise", "fear"]
-                    ),
-                }
-            ),
-            homepage=_HOMEPAGE,
-            citation=_CITATION,
-            task_templates=[TextClassification(text_column="tweet", label_column="label")],
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        data_dir = dl_manager.download_and_extract(_DOWNLOAD_URL)
-        return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_dir})]
-
-    def _generate_examples(self, filepath):
-        """Generate labeled arabic tweets examples for emoptions detection."""
-        with open(filepath, encoding="utf-8", mode="r") as csv_file:
-            next(csv_file)  # skip header
-            csv_reader = csv.reader(csv_file, quotechar='"', delimiter=",")
-
-            for id_, row in enumerate(csv_reader):
-                _, tweet, label = row
-                yield id_, {"tweet": tweet, "label": label}