Delete loading script

acronym_identification.py

@@ -1,93 +0,0 @@
-# coding=utf-8
-# Copyright 2020 HuggingFace Datasets Authors.
-#
-# 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.
-
-# Lint as: python3
-import json
-
-import datasets
-
-
-_DESCRIPTION = """\
-Acronym identification training and development sets for the acronym identification task at SDU@AAAI-21.
-"""
-_HOMEPAGE_URL = "https://github.com/amirveyseh/AAAI-21-SDU-shared-task-1-AI"
-_CITATION = """\
-@inproceedings{veyseh-et-al-2020-what,
-   title={{What Does This Acronym Mean? Introducing a New Dataset for Acronym Identification and Disambiguation}},
-   author={Amir Pouran Ben Veyseh and Franck Dernoncourt and Quan Hung Tran and Thien Huu Nguyen},
-   year={2020},
-   booktitle={Proceedings of COLING},
-   link={https://arxiv.org/pdf/2010.14678v1.pdf}
-}
-"""
-
-_TRAIN_URL = "https://raw.githubusercontent.com/amirveyseh/AAAI-21-SDU-shared-task-1-AI/master/dataset/train.json"
-_VALID_URL = "https://raw.githubusercontent.com/amirveyseh/AAAI-21-SDU-shared-task-1-AI/master/dataset/dev.json"
-_TEST_URL = "https://raw.githubusercontent.com/amirveyseh/AAAI-21-SDU-shared-task-1-AI/master/dataset/test.json"
-
-
-class AcronymIdentification(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "tokens": datasets.Sequence(datasets.Value("string")),
-                    "labels": datasets.Sequence(
-                        datasets.ClassLabel(names=["B-long", "B-short", "I-long", "I-short", "O"])
-                    ),
-                },
-            ),
-            supervised_keys=None,
-            homepage=_HOMEPAGE_URL,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        train_path = dl_manager.download_and_extract(_TRAIN_URL)
-        valid_path = dl_manager.download_and_extract(_VALID_URL)
-        test_path = dl_manager.download_and_extract(_TEST_URL)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"datapath": train_path, "datatype": "train"},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={"datapath": valid_path, "datatype": "valid"},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"datapath": test_path, "datatype": "test"},
-            ),
-        ]
-
-    def _generate_examples(self, datapath, datatype):
-        with open(datapath, encoding="utf-8") as f:
-            data = json.load(f)
-
-        for sentence_counter, d in enumerate(data):
-            resp = {
-                "id": d["id"],
-                "tokens": d["tokens"],
-            }
-            if datatype != "test":
-                resp["labels"] = d["labels"]
-            else:
-                resp["labels"] = ["O"] * len(d["tokens"])
-            yield sentence_counter, resp