Delete loading script

poem_sentiment.py

@@ -1,84 +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.
-"""Poem Sentiment: A sentiment dataset of poem verses"""
-
-
-import datasets
-
-
-_CITATION = """\
-@misc{sheng2020investigating,
-      title={Investigating Societal Biases in a Poetry Composition System},
-      author={Emily Sheng and David Uthus},
-      year={2020},
-      eprint={2011.02686},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL}
-}
-"""
-
-_DESCRIPTION = """\
-Poem Sentiment is a sentiment dataset of poem verses from Project Gutenberg. \
-This dataset can be used for tasks such as sentiment classification or style transfer for poems.
-"""
-
-
-_HOMEPAGE = "https://github.com/google-research-datasets/poem-sentiment"
-
-_BASE_URL = "https://raw.githubusercontent.com/google-research-datasets/poem-sentiment/master/data/"
-_URLS = {
-    "train": f"{_BASE_URL}/train.tsv",
-    "dev": f"{_BASE_URL}/dev.tsv",
-    "test": f"{_BASE_URL}/test.tsv",
-}
-_LABEL_MAPPING = {-1: 0, 0: 2, 1: 1, 2: 3}
-
-
-class PoemSentiment(datasets.GeneratorBasedBuilder):
-    """Poem Sentiment: A sentiment dataset of poem verses"""
-
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("int32"),
-                    "verse_text": datasets.Value("string"),
-                    "label": datasets.ClassLabel(names=["negative", "positive", "no_impact", "mixed"]),
-                }
-            ),
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        downloaded_files = dl_manager.download(_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:
-            lines = f.readlines()
-            for line in lines:
-                fields = line.strip().split("\t")
-                idx, verse_text, label = fields
-                label = _LABEL_MAPPING[int(label)]
-                yield int(idx), {"id": int(idx), "verse_text": verse_text, "label": label}