Delete loading script

samsum.py

@@ -1,112 +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.
-"""SAMSum dataset."""
-
-
-import json
-
-import py7zr
-
-import datasets
-
-
-_CITATION = """
-@article{gliwa2019samsum,
-  title={SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization},
-  author={Gliwa, Bogdan and Mochol, Iwona and Biesek, Maciej and Wawer, Aleksander},
-  journal={arXiv preprint arXiv:1911.12237},
-  year={2019}
-}
-"""
-
-_DESCRIPTION = """
-SAMSum Corpus contains over 16k chat dialogues with manually annotated
-summaries.
-There are two features:
-  - dialogue: text of dialogue.
-  - summary: human written summary of the dialogue.
-  - id: id of a example.
-"""
-
-_HOMEPAGE = "https://arxiv.org/abs/1911.12237"
-
-_LICENSE = "CC BY-NC-ND 4.0"
-
-_URL = "https://huggingface.co/datasets/samsum/resolve/main/data/corpus.7z"
-
-
-class Samsum(datasets.GeneratorBasedBuilder):
-    """SAMSum Corpus dataset."""
-
-    VERSION = datasets.Version("1.1.0")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="samsum"),
-    ]
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "id": datasets.Value("string"),
-                "dialogue": datasets.Value("string"),
-                "summary": datasets.Value("string"),
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        path = dl_manager.download(_URL)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "filepath": (path, "train.json"),
-                    "split": "train",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "filepath": (path, "test.json"),
-                    "split": "test",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "filepath": (path, "val.json"),
-                    "split": "val",
-                },
-            ),
-        ]
-
-    def _generate_examples(self, filepath, split):
-        """Yields examples."""
-        path, fname = filepath
-        with open(path, "rb") as f:
-            with py7zr.SevenZipFile(f, "r") as z:
-                for name, bio in z.readall().items():
-                    if name == fname:
-                        data = json.load(bio)
-        for example in data:
-            yield example["id"], example