Delete loading script

ar_sarcasm.py

@@ -1,110 +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.
-
-
-import csv
-import os
-
-import datasets
-
-
-# no BibTeX citation
-_CITATION = """@inproceedings{abu-farha-magdy-2020-arabic,
-    title = "From {A}rabic Sentiment Analysis to Sarcasm Detection: The {A}r{S}arcasm Dataset",
-    author = "Abu Farha, Ibrahim  and Magdy, Walid",
-    booktitle = "Proceedings of the 4th Workshop on Open-Source Arabic Corpora and Processing Tools, with a Shared Task on Offensive Language Detection",
-    month = may,
-    year = "2020",
-    address = "Marseille, France",
-    publisher = "European Language Resource Association",
-    url = "https://www.aclweb.org/anthology/2020.osact-1.5",
-    pages = "32--39",
-    language = "English",
-    ISBN = "979-10-95546-51-1",
-}"""
-
-_DESCRIPTION = """\
-ArSarcasm is a new Arabic sarcasm detection dataset.
-The dataset was created using previously available Arabic sentiment analysis datasets (SemEval 2017 and ASTD)
- and adds sarcasm and dialect labels to them. The dataset contains 10,547 tweets, 1,682 (16%) of which are sarcastic.
-"""
-
-_LICENSE = "MIT"
-
-# From: https://github.com/iabufarha/ArSarcasm/archive/master.zip
-_URLs = {
-    "default": "data.zip",
-}
-
-
-class ArSarcasm(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "dialect": datasets.ClassLabel(names=["egypt", "gulf", "levant", "magreb", "msa"]),
-                "sarcasm": datasets.ClassLabel(names=["non-sarcastic", "sarcastic"]),
-                "sentiment": datasets.ClassLabel(names=["negative", "neutral", "positive"]),
-                "original_sentiment": datasets.ClassLabel(names=["negative", "neutral", "positive"]),
-                "tweet": datasets.Value("string"),
-                "source": datasets.Value("string"),
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            supervised_keys=None,
-            homepage="https://github.com/iabufarha/ArSarcasm",
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        my_urls = _URLs[self.config.name]
-        data_dir = dl_manager.download_and_extract(my_urls)
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "ArSarcasm-master", "dataset", "ArSarcasm_train.csv"),
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "ArSarcasm-master", "dataset", "ArSarcasm_test.csv"),
-                },
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        with open(filepath, encoding="utf-8") as f:
-            rdr = csv.reader(f, delimiter=",")
-            next(rdr)
-            for id_, row in enumerate(rdr):
-                if len(row) < 6:
-                    continue
-                if row[4][0] == '"' and row[4][-1] == '"':
-                    row[4] = row[4][1:-1]
-                yield id_, {
-                    "dialect": row[0],
-                    "sarcasm": "sarcastic" if row[1] == "True" else "non-sarcastic",
-                    "sentiment": row[2],
-                    "original_sentiment": row[3],
-                    "tweet": row[4],
-                    "source": row[5],
-                }