Delete loading script

aslg_pc12.py

@@ -1,82 +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.
-"""ASLG-PC12: Synthetic English-ASL Gloss Parallel Corpus 2012"""
-
-
-import datasets
-
-
-_DESCRIPTION = """\
-A large synthetic collection of parallel English and ASL-Gloss texts.
-There are two string features: text, and gloss.
-"""
-
-_CITATION = """\
-@inproceedings{othman2012english,
-  title={English-asl gloss parallel corpus 2012: Aslg-pc12},
-  author={Othman, Achraf and Jemni, Mohamed},
-  booktitle={5th Workshop on the Representation and Processing of Sign Languages: Interactions between Corpus and Lexicon LREC},
-  year={2012}
-}
-"""
-
-_GLOSS_URL = "https://www.achrafothman.net/aslsmt/corpus/sample-corpus-asl-en.asl"
-_TEXT_URL = "https://www.achrafothman.net/aslsmt/corpus/sample-corpus-asl-en.en"
-
-_HOMEPAGE = "https://achrafothman.net/site/asl-smt/"
-
-
-class ASLGPC12(datasets.GeneratorBasedBuilder):
-    """ASLG-PC12: Synthetic English-ASL Gloss Parallel Corpus 2012"""
-
-    VERSION = datasets.Version("0.0.1")  # sample corpus
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            # This defines the different columns of the dataset and their types
-            features=datasets.Features(
-                {
-                    "gloss": datasets.Value("string"),  # American sign language gloss
-                    "text": datasets.Value("string"),  # English text
-                }
-            ),
-            homepage=_HOMEPAGE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-
-        gloss_path, text_path = dl_manager.download([_GLOSS_URL, _TEXT_URL])
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"gloss_path": gloss_path, "text_path": text_path},
-            )
-        ]
-
-    def _generate_examples(self, gloss_path, text_path):
-        """Yields examples."""
-
-        gloss_f = open(gloss_path, "r", encoding="utf-8")
-        text_f = open(text_path, "r", encoding="utf-8")
-
-        for i, (gloss, text) in enumerate(zip(gloss_f, text_f)):
-            yield i, {"gloss": gloss, "text": text}
-
-        gloss_f.close()
-        text_f.close()