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  1. offenseval_dravidian.py +0 -196
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- # coding=utf-8
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- # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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- #
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- # Licensed under the Apache License, Version 2.0 (the "License");
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- # you may not use this file except in compliance with the License.
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- # You may obtain a copy of the License at
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- #
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- # http://www.apache.org/licenses/LICENSE-2.0
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- #
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- # Unless required by applicable law or agreed to in writing, software
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- # distributed under the License is distributed on an "AS IS" BASIS,
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- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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- # See the License for the specific language governing permissions and
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- # limitations under the License.
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- """Offensive language identification in dravidian lanaguages dataset"""
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-
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-
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- import csv
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-
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- import datasets
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-
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-
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- _HOMEPAGE = "https://competitions.codalab.org/competitions/27654#learn_the_details"
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-
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-
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- _CITATION = """\
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- @inproceedings{dravidianoffensive-eacl,
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- title={Findings of the Shared Task on {O}ffensive {L}anguage {I}dentification in {T}amil, {M}alayalam, and {K}annada},
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- author={Chakravarthi, Bharathi Raja and
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- Priyadharshini, Ruba and
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- Jose, Navya and
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- M, Anand Kumar and
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- Mandl, Thomas and
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- Kumaresan, Prasanna Kumar and
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- Ponnsamy, Rahul and
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- V,Hariharan and
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- Sherly, Elizabeth and
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- McCrae, John Philip },
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- booktitle = "Proceedings of the First Workshop on Speech and Language Technologies for Dravidian Languages",
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- month = April,
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- year = "2021",
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- publisher = "Association for Computational Linguistics",
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- year={2021}
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- }
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- """
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-
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- _DESCRIPTION = """\
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- 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.
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- """
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-
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- _LICENSE = "Creative Commons Attribution 4.0 International Licence"
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-
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- _URLs = {
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- "tamil": {
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- "TRAIN_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=15auwrFAlq52JJ61u7eSfnhT9rZtI5sjk&export=download",
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- "VALIDATION_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=1Jme-Oftjm7OgfMNLKQs1mO_cnsQmznRI&export=download",
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- },
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- "malayalam": {
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- "TRAIN_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=13JCCr-IjZK7uhbLXeufptr_AxvsKinVl&export=download",
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- "VALIDATION_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=1J0msLpLoM6gmXkjC6DFeQ8CG_rrLvjnM&export=download",
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- },
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- "kannada": {
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- "TRAIN_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=1BFYF05rx-DK9Eb5hgoIgd6EcB8zOI-zu&export=download",
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- "VALIDATION_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=1V077dMQvscqpUmcWTcFHqRa_vTy-bQ4H&export=download",
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- },
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- }
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-
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-
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- class OffensevalDravidian(datasets.GeneratorBasedBuilder):
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- """Offensive language identification in dravidian lanaguages dataset"""
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-
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- VERSION = datasets.Version("1.0.0")
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-
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- BUILDER_CONFIGS = [
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- datasets.BuilderConfig(
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- name="tamil", version=VERSION, description="This part of my dataset covers Tamil dataset"
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- ),
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- datasets.BuilderConfig(
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- name="malayalam", version=VERSION, description="This part of my dataset covers Malayalam dataset"
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- ),
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- datasets.BuilderConfig(
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- name="kannada", version=VERSION, description="This part of my dataset covers Kannada dataset"
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- ),
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- ]
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-
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- def _info(self):
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-
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- if self.config.name == "tamil": # This is the name of the configuration selected in BUILDER_CONFIGS above
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- features = datasets.Features(
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- {
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- "text": datasets.Value("string"),
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- "label": datasets.features.ClassLabel(
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- names=[
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- "Not_offensive",
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- "Offensive_Untargetede",
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- "Offensive_Targeted_Insult_Individual",
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- "Offensive_Targeted_Insult_Group",
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- "Offensive_Targeted_Insult_Other",
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- "not-Tamil",
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- ]
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- ),
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- }
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- )
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- elif self.config.name == "malayalam":
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- features = datasets.Features(
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- {
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- "text": datasets.Value("string"),
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- "label": datasets.features.ClassLabel(
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- names=[
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- "Not_offensive",
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- "Offensive_Untargetede",
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- "Offensive_Targeted_Insult_Individual",
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- "Offensive_Targeted_Insult_Group",
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- "Offensive_Targeted_Insult_Other",
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- "not-malayalam",
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- ]
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- ),
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- }
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- )
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-
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- # else self.config.name == "kannada":
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- else:
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- features = datasets.Features(
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- {
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- "text": datasets.Value("string"),
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- "label": datasets.features.ClassLabel(
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- names=[
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- "Not_offensive",
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- "Offensive_Untargetede",
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- "Offensive_Targeted_Insult_Individual",
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- "Offensive_Targeted_Insult_Group",
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- "Offensive_Targeted_Insult_Other",
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- "not-Kannada",
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- ]
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- ),
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- }
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- )
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-
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- return datasets.DatasetInfo(
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- # This is the description that will appear on the datasets page.
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- description=_DESCRIPTION,
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- # This defines the different columns of the dataset and their types
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- features=features, # Here we define them above because they are different between the two configurations
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- # If there's a common (input, target) tuple from the features,
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- # specify them here. They'll be used if as_supervised=True in
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- # builder.as_dataset.
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- supervised_keys=None,
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- # Homepage of the dataset for documentation
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- homepage=_HOMEPAGE,
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- # License for the dataset if available
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- license=_LICENSE,
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- # Citation for the dataset
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- citation=_CITATION,
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- )
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-
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- def _split_generators(self, dl_manager):
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- """Returns SplitGenerators."""
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-
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- my_urls = _URLs[self.config.name]
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-
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- train_path = dl_manager.download_and_extract(my_urls["TRAIN_DOWNLOAD_URL"])
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- validation_path = dl_manager.download_and_extract(my_urls["VALIDATION_DOWNLOAD_URL"])
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-
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- return [
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- datasets.SplitGenerator(
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- name=datasets.Split.TRAIN,
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- gen_kwargs={
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- "filepath": train_path,
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- "split": "train",
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- },
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- ),
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- datasets.SplitGenerator(
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- name=datasets.Split.VALIDATION,
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- gen_kwargs={
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- "filepath": validation_path,
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- "split": "validation",
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- },
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- ),
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- ]
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-
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- def _generate_examples(self, filepath, split):
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- """Generate Offenseval_dravidian examples."""
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-
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- with open(filepath, encoding="utf-8") as csv_file:
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- csv_reader = csv.reader(
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- csv_file, quotechar='"', delimiter="\t", quoting=csv.QUOTE_ALL, skipinitialspace=False
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- )
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-
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- for id_, row in enumerate(csv_reader):
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-
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- if self.config.name == "kannada":
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- text, label = row
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- else:
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- text, label, dummy = row
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-
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- yield id_, {"text": text, "label": label}