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-# 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: Address all TODOs and remove all explanatory comments
-"""DUVEL : the Detection of Unlimited Variant Ensemble in Literature"""
-
-
-import csv
-import datasets
-
-
-# TODO: Add BibTeX citation
-# Find for instance the citation on arxiv or on the dataset repo/website
-_CITATION = """\
-@InProceedings{huggingface:dataset,
-title = {A great new dataset},
-author={huggingface, Inc.
-},
-year={2020}
-}
-"""
-
-
-_DESCRIPTION = """\
-This dataset was created to identity oligogenic variant combinations, i.e. relation between several genes and their mutations, \
-causing genetic diseases in scientific articles written in english. At the moment, it contains only digenic variant combinations, \
-i.e. relations between two genes and at least two variants. The dataset is intended for binary relation extraction where the \
-entities are masked within the text.
-"""
-
-_HOMEPAGE = "https://github.com/cnachteg/DUVEL"
-
-_LICENSE = "cc-by-nc-sa-4.0"
-
-# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
-# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
-_URL = "https://raw.githubusercontent.com/cnachteg/DUVEL/main/"
-_URLS = {
-    "train": _URL + "data/train.csv",
-    "dev": _URL + "data/validation.csv",
-    "test": _URL + "data/test.csv"
-}
-
-
-
-class DUVEL(datasets.GeneratorBasedBuilder):
-    """DUVEL : the Detection of Unlimited Variant Ensemble in Literature - Version 1.1."""
-
-    VERSION = datasets.Version("1.1.0")
-    
-    def _info(self):
-        features = datasets.Features(
-                {
-                    'sentence': datasets.Value('string'),
-                    'pmcid': datasets.Value('int32'), 
-                    'gene1': datasets.Value('string'),
-                    'gene2': datasets.Value('string'), 
-                    'variant1': datasets.Value('string'), 
-                    'variant2': datasets.Value('string'),
-                    'label': datasets.ClassLabel(names=[0,1])
-                }
-            )
-        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, uncomment supervised_keys line below and
-            # specify them. They'll be used if as_supervised=True in builder.as_dataset.
-            # supervised_keys=("sentence", "label"),
-            # Homepage of the dataset for documentation
-            homepage=_HOMEPAGE,
-            # License for the dataset if available
-            license=_LICENSE,
-            # Citation for the dataset
-            citation=_CITATION,
-            task_templates=[
-                datasets.tasks.TextClassification(
-                    text_column='sentence', label_column='label'
-                )
-            ],
-        )
-
-    def _split_generators(self, dl_manager):
-        downloaded_files = dl_manager.download_and_extract(_URLS)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "filepath": downloaded_files['train']
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "filepath": downloaded_files['dev'],
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "filepath": downloaded_files['test'],
-                },
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        with open(filepath, encoding="utf-8") as f:
-            reader = csv.DictReader(f)
-            for key, row in enumerate(reader):
-                yield key, row