Convert dataset to Parquet (#2)

- Convert dataset to Parquet (4f6106b3e6410b27c587e104123e9fb3c782730e)
- Delete loading script (19d107eb1bed1c70540d3e907fca61e8400d22fb)

README.md

@@ -19,23 +19,28 @@ task_categories:
 task_ids:
 - language-modeling
 - masked-language-modeling
-paperswithcode_id: null
 pretty_name: Tashkeela
 tags:
 - diacritics-prediction
 dataset_info:
+  config_name: plain_text
   features:
-  - name: text
-    dtype: string
   - name: book
     dtype: string
-  config_name: plain_text
+  - name: text
+    dtype: string
   splits:
   - name: train
-    num_bytes: 1081110249
+    num_bytes: 1081110229
     num_examples: 97
-  download_size: 183393530
-  dataset_size: 1081110249
+  download_size: 420434207
+  dataset_size: 1081110229
+configs:
+- config_name: plain_text
+  data_files:
+  - split: train
+    path: plain_text/train-*
+  default: true
 ---
 
 # Dataset Card for Tashkeela

plain_text/train-00000-of-00003.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e7b5cc918e9b1e09060e5eca812dd44efa73d9682da997b03f4364d13031fe31
+size 138891011

plain_text/train-00001-of-00003.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7c72edc5cb177e8a00059db6d173b4a54faf94f27908b23e42f3d0caa9251fd3
+size 180319094

plain_text/train-00002-of-00003.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:991556a9e4165089f1c0ae13e229573434a6603c260ff4bf3c9e4e0eb094ea2c
+size 101224102

tashkeela.py

@@ -1,104 +0,0 @@
-# coding=utf-8
-# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
-#
-# 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.
-
-# Lint as: python3
-"""Arabic Vocalized Words Dataset."""
-
-
-import glob
-import os
-
-import datasets
-
-
-_DESCRIPTION = """\
-Arabic vocalized texts.
-it contains 75 million of fully vocalized words mainly\
-97 books from classical and modern Arabic language.
-"""
-
-_CITATION = """\
-@article{zerrouki2017tashkeela,
-  title={Tashkeela: Novel corpus of Arabic vocalized texts, data for auto-diacritization systems},
-  author={Zerrouki, Taha and Balla, Amar},
-  journal={Data in brief},
-  volume={11},
-  pages={147},
-  year={2017},
-  publisher={Elsevier}
-}
-"""
-
-_HOMEPAGE = "https://sourceforge.net/projects/tashkeela/"
-
-_LICENSE = "GPLv2"
-
-_DOWNLOAD_URL = "https://sourceforge.net/projects/tashkeela/files/latest/download"
-
-
-class TashkeelaConfig(datasets.BuilderConfig):
-    """BuilderConfig for Tashkeela."""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for Tashkeela.
-
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(TashkeelaConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
-
-
-class Tashkeela(datasets.GeneratorBasedBuilder):
-    """Tashkeela dataset."""
-
-    BUILDER_CONFIGS = [
-        TashkeelaConfig(
-            name="plain_text",
-            description="Plain text",
-        )
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "book": datasets.Value("string"),
-                    "text": datasets.Value("string"),
-                }
-            ),
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        arch_path = dl_manager.download_and_extract(_DOWNLOAD_URL)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "directory": os.path.join(arch_path, "Tashkeela-arabic-diacritized-text-utf8-0.3", "texts.txt")
-                },
-            ),
-        ]
-
-    def _generate_examples(self, directory):
-        """Generate examples."""
-
-        for id_, file_name in enumerate(sorted(glob.glob(os.path.join(directory, "**.txt")))):
-            with open(file_name, encoding="UTF-8") as f:
-                yield str(id_), {"book": file_name, "text": f.read().strip()}