Delete loading script

offenseval_dravidian.py

@@ -1,196 +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.
-"""Offensive language identification in dravidian lanaguages dataset"""
-
-
-import csv
-
-import datasets
-
-
-_HOMEPAGE = "https://competitions.codalab.org/competitions/27654#learn_the_details"
-
-
-_CITATION = """\
-@inproceedings{dravidianoffensive-eacl,
-title={Findings of the Shared Task on {O}ffensive {L}anguage {I}dentification in {T}amil, {M}alayalam, and {K}annada},
-author={Chakravarthi, Bharathi Raja and
-Priyadharshini, Ruba and
-Jose, Navya and
-M, Anand Kumar and
-Mandl, Thomas and
-Kumaresan, Prasanna Kumar and
-Ponnsamy, Rahul and
-V,Hariharan and
-Sherly, Elizabeth and
-McCrae, John Philip },
-booktitle = "Proceedings of the First Workshop on Speech and Language Technologies for Dravidian Languages",
-month = April,
-year = "2021",
-publisher = "Association for Computational Linguistics",
-year={2021}
-}
-"""
-
-_DESCRIPTION = """\
-Offensive language identification in dravidian lanaguages dataset. The goal of this task is to identify offensive language content of the code-mixed dataset of comments/posts in Dravidian Languages ( (Tamil-English, Malayalam-English, and Kannada-English)) collected from social media.
-"""
-
-_LICENSE = "Creative Commons Attribution 4.0 International Licence"
-
-_URLs = {
-    "tamil": {
-        "TRAIN_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=15auwrFAlq52JJ61u7eSfnhT9rZtI5sjk&export=download",
-        "VALIDATION_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=1Jme-Oftjm7OgfMNLKQs1mO_cnsQmznRI&export=download",
-    },
-    "malayalam": {
-        "TRAIN_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=13JCCr-IjZK7uhbLXeufptr_AxvsKinVl&export=download",
-        "VALIDATION_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=1J0msLpLoM6gmXkjC6DFeQ8CG_rrLvjnM&export=download",
-    },
-    "kannada": {
-        "TRAIN_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=1BFYF05rx-DK9Eb5hgoIgd6EcB8zOI-zu&export=download",
-        "VALIDATION_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=1V077dMQvscqpUmcWTcFHqRa_vTy-bQ4H&export=download",
-    },
-}
-
-
-class OffensevalDravidian(datasets.GeneratorBasedBuilder):
-    """Offensive language identification in dravidian lanaguages dataset"""
-
-    VERSION = datasets.Version("1.0.0")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name="tamil", version=VERSION, description="This part of my dataset covers Tamil dataset"
-        ),
-        datasets.BuilderConfig(
-            name="malayalam", version=VERSION, description="This part of my dataset covers Malayalam dataset"
-        ),
-        datasets.BuilderConfig(
-            name="kannada", version=VERSION, description="This part of my dataset covers Kannada dataset"
-        ),
-    ]
-
-    def _info(self):
-
-        if self.config.name == "tamil":  # This is the name of the configuration selected in BUILDER_CONFIGS above
-            features = datasets.Features(
-                {
-                    "text": datasets.Value("string"),
-                    "label": datasets.features.ClassLabel(
-                        names=[
-                            "Not_offensive",
-                            "Offensive_Untargetede",
-                            "Offensive_Targeted_Insult_Individual",
-                            "Offensive_Targeted_Insult_Group",
-                            "Offensive_Targeted_Insult_Other",
-                            "not-Tamil",
-                        ]
-                    ),
-                }
-            )
-        elif self.config.name == "malayalam":
-            features = datasets.Features(
-                {
-                    "text": datasets.Value("string"),
-                    "label": datasets.features.ClassLabel(
-                        names=[
-                            "Not_offensive",
-                            "Offensive_Untargetede",
-                            "Offensive_Targeted_Insult_Individual",
-                            "Offensive_Targeted_Insult_Group",
-                            "Offensive_Targeted_Insult_Other",
-                            "not-malayalam",
-                        ]
-                    ),
-                }
-            )
-
-        # else self.config.name == "kannada":
-        else:
-            features = datasets.Features(
-                {
-                    "text": datasets.Value("string"),
-                    "label": datasets.features.ClassLabel(
-                        names=[
-                            "Not_offensive",
-                            "Offensive_Untargetede",
-                            "Offensive_Targeted_Insult_Individual",
-                            "Offensive_Targeted_Insult_Group",
-                            "Offensive_Targeted_Insult_Other",
-                            "not-Kannada",
-                        ]
-                    ),
-                }
-            )
-
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # This defines the different columns of the dataset and their types
-            features=features,  # Here we define them above because they are different between the two configurations
-            # If there's a common (input, target) tuple from the features,
-            # specify them here. They'll be used if as_supervised=True in
-            # builder.as_dataset.
-            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."""
-
-        my_urls = _URLs[self.config.name]
-
-        train_path = dl_manager.download_and_extract(my_urls["TRAIN_DOWNLOAD_URL"])
-        validation_path = dl_manager.download_and_extract(my_urls["VALIDATION_DOWNLOAD_URL"])
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "filepath": train_path,
-                    "split": "train",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "filepath": validation_path,
-                    "split": "validation",
-                },
-            ),
-        ]
-
-    def _generate_examples(self, filepath, split):
-        """Generate Offenseval_dravidian examples."""
-
-        with open(filepath, encoding="utf-8") as csv_file:
-            csv_reader = csv.reader(
-                csv_file, quotechar='"', delimiter="\t", quoting=csv.QUOTE_ALL, skipinitialspace=False
-            )
-
-            for id_, row in enumerate(csv_reader):
-
-                if self.config.name == "kannada":
-                    text, label = row
-                else:
-                    text, label, dummy = row
-
-                yield id_, {"text": text, "label": label}