Delete wiki40b.py

wiki40b.py

@@ -1,182 +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.
-
-"""Wiki40B: A clean Wikipedia dataset for 40+ languages."""
-
-
-import datasets
-
-
-logger = datasets.logging.get_logger(__name__)
-
-
-_CITATION = """
-"""
-
-_DESCRIPTION = """
-Clean-up text for 40+ Wikipedia languages editions of pages
-correspond to entities. The datasets have train/dev/test splits per language.
-The dataset is cleaned up by page filtering to remove disambiguation pages,
-redirect pages, deleted pages, and non-entity pages. Each example contains the
-wikidata id of the entity, and the full Wikipedia article after page processing
-that removes non-content sections and structured objects.
-"""
-
-_LICENSE = """
-This work is licensed under the Creative Commons Attribution-ShareAlike
-3.0 Unported License. To view a copy of this license, visit
-http://creativecommons.org/licenses/by-sa/3.0/ or send a letter to
-Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.
-"""
-
-_URL = "https://research.google/pubs/pub49029/"
-
-_DATA_DIRECTORY = "gs://tfds-data/downloads/wiki40b/tfrecord_prod"
-
-WIKIPEDIA_LANGUAGES = [
-    "en",
-    "ar",
-    "zh-cn",
-    "zh-tw",
-    "nl",
-    "fr",
-    "de",
-    "it",
-    "ja",
-    "ko",
-    "pl",
-    "pt",
-    "ru",
-    "es",
-    "th",
-    "tr",
-    "bg",
-    "ca",
-    "cs",
-    "da",
-    "el",
-    "et",
-    "fa",
-    "fi",
-    "he",
-    "hi",
-    "hr",
-    "hu",
-    "id",
-    "lt",
-    "lv",
-    "ms",
-    "no",
-    "ro",
-    "sk",
-    "sl",
-    "sr",
-    "sv",
-    "tl",
-    "uk",
-    "vi",
-]
-
-
-class Wiki40bConfig(datasets.BuilderConfig):
-    """BuilderConfig for Wiki40B."""
-
-    def __init__(self, language=None, **kwargs):
-        """BuilderConfig for Wiki40B.
-
-        Args:
-          language: string, the language code for the Wiki40B dataset to use.
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(Wiki40bConfig, self).__init__(
-            name=str(language), description=f"Wiki40B dataset for {language}.", **kwargs
-        )
-        self.language = language
-
-
-_VERSION = datasets.Version("1.1.0")
-
-
-class Wiki40b(datasets.BeamBasedBuilder):
-    """Wiki40B: A Clean Wikipedia Dataset for Mutlilingual Language Modeling."""
-
-    BUILDER_CONFIGS = [
-        Wiki40bConfig(
-            version=_VERSION,
-            language=lang,
-        )  # pylint:disable=g-complex-comprehension
-        for lang in WIKIPEDIA_LANGUAGES
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "wikidata_id": datasets.Value("string"),
-                    "text": datasets.Value("string"),
-                    "version_id": datasets.Value("string"),
-                }
-            ),
-            supervised_keys=None,
-            homepage=_URL,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-
-        lang = self.config.language
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"filepaths": f"{_DATA_DIRECTORY}/train/{lang}_examples-*"},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={"filepaths": f"{_DATA_DIRECTORY}/dev/{lang}_examples-*"},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"filepaths": f"{_DATA_DIRECTORY}/test/{lang}_examples-*"},
-            ),
-        ]
-
-    def _build_pcollection(self, pipeline, filepaths):
-        """Build PCollection of examples."""
-        import apache_beam as beam
-        import tensorflow as tf
-
-        logger.info("generating examples from = %s", filepaths)
-
-        def _extract_content(example):
-            """Extracts content from a TFExample."""
-            wikidata_id = example.features.feature["wikidata_id"].bytes_list.value[0].decode("utf-8")
-            text = example.features.feature["text"].bytes_list.value[0].decode("utf-8")
-            version_id = example.features.feature["version_id"].bytes_list.value[0].decode("utf-8")
-
-            # wikidata_id could be duplicated with different texts.
-            yield wikidata_id + text, {
-                "wikidata_id": wikidata_id,
-                "text": text,
-                "version_id": version_id,
-            }
-
-        return (
-            pipeline
-            | beam.io.ReadFromTFRecord(filepaths, coder=beam.coders.ProtoCoder(tf.train.Example))
-            | beam.FlatMap(_extract_content)
-        )