Delete loading script

covid_dialogue.py

@@ -1,105 +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.
-"""Covid Dialog dataset in English and Chinese"""
-
-
-import copy
-import os
-import re
-import textwrap
-
-import datasets
-
-
-# BibTeX citation
-_CITATION = """\
-@article{ju2020CovidDialog,
-  title={CovidDialog: Medical Dialogue Datasets about COVID-19},
-  author={Ju, Zeqian and Chakravorty, Subrato and He, Xuehai and Chen, Shu and Yang, Xingyi and Xie, Pengtao},
-  journal={ https://github.com/UCSD-AI4H/COVID-Dialogue},
-  year={2020}
-}
-"""
-
-# Official description of the dataset
-_DESCRIPTION = textwrap.dedent(
-    """
-    COVID-Dialogue-Dataset is amedical dialogue dataset about COVID-19 and other types of pneumonia.
-    Patients who are concerned that they may be infected by COVID-19 or other pneumonia consult doctors and doctors provide advice.
-    There are 603 consultations in English and 1393 consultations in Chinese.
-    """
-)
-
-# Link to an official homepage for the dataset here
-_HOMEPAGE = "https://github.com/UCSD-AI4H/COVID-Dialogue"
-
-_LICENSE = ""
-
-
-import datasets
-import os
-import json
-
-
-class CovidDialogueHelm(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.0.0")
-
-    BUILDER_CONFIGS = [datasets.BuilderConfig(name="default", version=datasets.Version("1.0.0"), description=_DESCRIPTION)]
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "query": datasets.Value("string"),
-                "answer": datasets.Value("string"),
-            }
-        )
-        return datasets.DatasetInfo(
-            description=f"Covid Dialogue dataset, as preprocessed and shuffled in HELM",
-            features=features,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        test_target = dl_manager.download("test.source")
-        test_source = dl_manager.download("test.source")
-        train_source = dl_manager.download("train.source")
-        train_target = dl_manager.download("train.target")
-        val_source = dl_manager.download("val.source")
-        val_target = dl_manager.download("val.target")
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"target": train_target, "source": train_source},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={"target": val_target, "source": val_source},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"target": test_target, "source": test_source},
-            ),
-        ]
-
-    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
-    def _generate_examples(self, source, target):
-        with open(source, encoding="utf-8") as f_source:
-            with open(target, encoding="utf-8") as f_target:
-                for idx, (s, t) in enumerate(zip(f_source, f_target)):
-                    yield idx, {"query": s, "answer": t}
-