Delete loading script

eu_regulatory_ir.py

@@ -1,149 +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.
-"""EURegIR: Regulatory Compliance IR (EU/UK)"""
-
-
-import json
-import os
-
-import datasets
-
-
-_CITATION = """\
-@inproceedings{chalkidis-etal-2021-regir,
-    title = "Regulatory Compliance through Doc2Doc Information Retrieval: A case study in EU/UK legislation where text similarity has limitations",
-    author = "Chalkidis, Ilias  and Fergadiotis, Emmanouil and Manginas, Nikos and Katakalou, Eva,  and Malakasiotis, Prodromos",
-    booktitle = "Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021)",
-    year = "2021",
-    address = "Online",
-    publisher = "Association for Computational Linguistics",
-    url = "https://arxiv.org/abs/2101.10726",
-}
-"""
-
-_DESCRIPTION = """\
-EURegIR: Regulatory Compliance IR (EU/UK)
-"""
-
-_HOMEPAGE = "https://archive.org/details/eacl2021_regir_dataset"
-
-_LICENSE = "CC BY-SA (Creative Commons / Attribution-ShareAlike)"
-
-_URLs = {
-    "eu2uk": "https://archive.org/download/eacl2021_regir_datasets/eu2uk.zip",
-    "uk2eu": "https://archive.org/download/eacl2021_regir_datasets/uk2eu.zip",
-}
-
-
-class EuRegulatoryIr(datasets.GeneratorBasedBuilder):
-    """EURegIR: Regulatory Compliance IR (EU/UK)"""
-
-    VERSION = datasets.Version("1.1.0")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="eu2uk", version=VERSION, description="EURegIR: Regulatory Compliance IR (EU2UK)"),
-        datasets.BuilderConfig(name="uk2eu", version=VERSION, description="EURegIR: Regulatory Compliance IR (UK2EU)"),
-    ]
-
-    def _info(self):
-        if self.config.name == "eu2uk":
-            features = datasets.Features(
-                {
-                    "document_id": datasets.Value("string"),
-                    "publication_year": datasets.Value("string"),
-                    "text": datasets.Value("string"),
-                    "relevant_documents": datasets.features.Sequence(datasets.Value("string")),
-                }
-            )
-        else:
-            features = datasets.Features(
-                {
-                    "document_id": datasets.Value("string"),
-                    "publication_year": datasets.Value("string"),
-                    "text": datasets.Value("string"),
-                    "relevant_documents": datasets.features.Sequence(datasets.Value("string")),
-                }
-            )
-        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]
-        data_dir = dl_manager.download_and_extract(my_urls)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "train.jsonl"),
-                    "split": "train",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(data_dir, "test.jsonl"), "split": "test"},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "dev.jsonl"),
-                    "split": "dev",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=f"{self.config.name.split('2')[1]}_corpus",
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "corpus.jsonl"),
-                    "split": f"{self.config.name.split('2')[1]}_corpus",
-                },
-            ),
-        ]
-
-    def _generate_examples(
-        self, filepath, split  # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
-    ):
-        """Yields examples as (key, example) tuples."""
-        # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
-        # The `key` is here for legacy reason (tfds) and is not important in itself.
-
-        with open(filepath, encoding="utf-8") as f:
-            for id_, row in enumerate(f):
-                data = json.loads(row)
-                yield id_, {
-                    "document_id": data["document_id"],
-                    "text": data["text"],
-                    "publication_year": data["publication_year"],
-                    "relevant_documents": data["relevant_documents"]
-                    if split != f"{self.config.name.split('2')[1]}_corpus"
-                    else [],
-                }