Delete loading script

allegro_reviews.py

@@ -1,109 +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.
-"""Allegro Reviews dataset"""
-
-
-import csv
-import os
-
-import datasets
-
-
-_CITATION = """\
-@inproceedings{rybak-etal-2020-klej,
-    title = "{KLEJ}: Comprehensive Benchmark for Polish Language Understanding",
-    author = "Rybak, Piotr and Mroczkowski, Robert and Tracz, Janusz and Gawlik, Ireneusz",
-    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
-    month = jul,
-    year = "2020",
-    address = "Online",
-    publisher = "Association for Computational Linguistics",
-    url = "https://www.aclweb.org/anthology/2020.acl-main.111",
-    pages = "1191--1201",
-}
-"""
-
-_DESCRIPTION = """\
-Allegro Reviews is a sentiment analysis dataset, consisting of 11,588 product reviews written in Polish and extracted
-from Allegro.pl - a popular e-commerce marketplace. Each review contains at least 50 words and has a rating on a scale
-from one (negative review) to five (positive review).
-
-We recommend using the provided train/dev/test split. The ratings for the test set reviews are kept hidden.
-You can evaluate your model using the online evaluation tool available on klejbenchmark.com.
-"""
-
-_HOMEPAGE = "https://github.com/allegro/klejbenchmark-allegroreviews"
-
-_LICENSE = "CC BY-SA 4.0"
-
-_URLs = "https://klejbenchmark.com/static/data/klej_ar.zip"
-
-
-class AllegroReviews(datasets.GeneratorBasedBuilder):
-    """
-    Allegro Reviews is a sentiment analysis dataset, consisting of 11,588 product reviews written in Polish
-    and extracted from Allegro.pl - a popular e-commerce marketplace.
-    """
-
-    VERSION = datasets.Version("1.1.0")
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "text": datasets.Value("string"),
-                    "rating": datasets.Value("float"),
-                }
-            ),
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        data_dir = dl_manager.download_and_extract(_URLs)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "train.tsv"),
-                    "split": "train",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"filepath": os.path.join(data_dir, "test_features.tsv"), "split": "test"},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "dev.tsv"),
-                    "split": "dev",
-                },
-            ),
-        ]
-
-    def _generate_examples(self, filepath, split):
-        """Yields examples."""
-        with open(filepath, encoding="utf-8") as f:
-            reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
-            for id_, row in enumerate(reader):
-                yield id_, {
-                    "text": row["text"],
-                    "rating": "-1" if split == "test" else row["rating"],
-                }