Delete loading script

turk.py

@@ -1,117 +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.
-"""TURKCorpus: a dataset for sentence simplification evaluation"""
-
-
-import datasets
-
-
-_CITATION = """\
- @article{Xu-EtAl:2016:TACL,
- author = {Wei Xu and Courtney Napoles and Ellie Pavlick and Quanze Chen and Chris Callison-Burch},
- title = {Optimizing Statistical Machine Translation for Text Simplification},
- journal = {Transactions of the Association for Computational Linguistics},
- volume = {4},
- year = {2016},
- url = {https://cocoxu.github.io/publications/tacl2016-smt-simplification.pdf},
- pages = {401--415}
- }
-}
-"""
-
-_DESCRIPTION = """\
-TURKCorpus is a dataset for evaluating sentence simplification systems that focus on lexical paraphrasing,
-as described in "Optimizing Statistical Machine Translation for Text Simplification". The corpus is composed of 2000 validation and 359 test original sentences that were each simplified 8 times by different annotators.
-"""
-
-_HOMEPAGE = "https://github.com/cocoxu/simplification"
-
-_LICENSE = "GNU General Public License v3.0"
-
-_URL_LIST = [
-    (
-        "test.8turkers.tok.norm",
-        "https://raw.githubusercontent.com/cocoxu/simplification/master/data/turkcorpus/test.8turkers.tok.norm",
-    ),
-    (
-        "tune.8turkers.tok.norm",
-        "https://raw.githubusercontent.com/cocoxu/simplification/master/data/turkcorpus/tune.8turkers.tok.norm",
-    ),
-]
-_URL_LIST += [
-    (
-        f"{spl}.8turkers.tok.turk.{i}",
-        f"https://raw.githubusercontent.com/cocoxu/simplification/master/data/turkcorpus/{spl}.8turkers.tok.turk.{i}",
-    )
-    for spl in ["tune", "test"]
-    for i in range(8)
-]
-
-_URLs = dict(_URL_LIST)
-
-
-class Turk(datasets.GeneratorBasedBuilder):
-
-    VERSION = datasets.Version("1.0.0")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name="simplification",
-            version=VERSION,
-            description="A set of original sentences aligned with 8 possible simplifications for each.",
-        )
-    ]
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "original": datasets.Value("string"),
-                "simplifications": datasets.Sequence(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):
-        data_dir = dl_manager.download_and_extract(_URLs)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "filepaths": data_dir,
-                    "split": "valid",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"filepaths": data_dir, "split": "test"},
-            ),
-        ]
-
-    def _generate_examples(self, filepaths, split):
-        """Yields examples."""
-        if split == "valid":
-            split = "tune"
-        files = [open(filepaths[f"{split}.8turkers.tok.norm"], encoding="utf-8")] + [
-            open(filepaths[f"{split}.8turkers.tok.turk.{i}"], encoding="utf-8") for i in range(8)
-        ]
-        for id_, lines in enumerate(zip(*files)):
-            yield id_, {"original": lines[0].strip(), "simplifications": [line.strip() for line in lines[1:]]}