Delete loading script

wongnai_reviews.py

@@ -1,76 +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.
-"""TODO: Add a description here."""
-
-
-import csv
-import os
-
-import datasets
-from datasets.tasks import TextClassification
-
-
-# no BibTeX citation
-_CITATION = ""
-
-_DESCRIPTION = """\
-Wongnai's review dataset contains restaurant reviews and ratings, mainly in Thai language.
-The reviews are in 5 classes ranging from 1 to 5 stars.
-"""
-
-_LICENSE = "LGPL-3.0"
-
-_URLs = {"default": "https://archive.org/download/wongnai_reviews/wongnai_reviews_withtest.zip"}
-
-
-class WongnaiReviews(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.0.1")
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "review_body": datasets.Value("string"),
-                "star_rating": datasets.features.ClassLabel(names=["1", "2", "3", "4", "5"]),
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            supervised_keys=None,
-            homepage="https://github.com/wongnai/wongnai-corpus",
-            license=_LICENSE,
-            citation=_CITATION,
-            task_templates=[TextClassification(text_column="review_body", label_column="star_rating")],
-        )
-
-    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, "w_review_train.csv"), "split": "train"},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"filepath": os.path.join(data_dir, "w_review_test.csv"), "split": "test"},
-            ),
-        ]
-
-    def _generate_examples(self, filepath, split):
-        with open(filepath, encoding="utf-8") as f:
-            spamreader = csv.reader(f, delimiter=";", quotechar='"')
-            for id_, row in enumerate(spamreader):
-                yield id_, {"review_body": row[0], "star_rating": row[1]}