Update files from the datasets library (from 1.0.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.0.0

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
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dummy/all/1.2.0/dummy_data.zip

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+size 2840

dummy/sep/1.2.0/dummy_data.zip

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+size 1665

urls_checksums/checksums.txt

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+https://raw.githubusercontent.com/mahnazkoupaee/WikiHow-Dataset/master/all_test.txt 182146 c7b3037410bdfbed258cf96dcd5e7d04bc7432b9c20c6e6cd8063b6db84f8f94
+https://raw.githubusercontent.com/mahnazkoupaee/WikiHow-Dataset/master/all_train.txt 5096074 149bdd47ca9607bc5c730805d01c8fd879ffd7f328fd6869e6109288e8cfe733
+https://raw.githubusercontent.com/mahnazkoupaee/WikiHow-Dataset/master/all_val.txt 182165 759789579a0a96783f054387d5c2d7b537db75f462629116743f0ac3e7450be4

wikihow.py

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+# 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
+"""WikiHow Datasets."""
+
+from __future__ import absolute_import, division, print_function
+
+import csv
+import os
+import re
+
+import datasets
+
+
+_CITATION = """
+@misc{koupaee2018wikihow,
+    title={WikiHow: A Large Scale Text Summarization Dataset},
+    author={Mahnaz Koupaee and William Yang Wang},
+    year={2018},
+    eprint={1810.09305},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """
+WikiHow is a new large-scale dataset using the online WikiHow
+(http://www.wikihow.com/) knowledge base.
+
+There are two features:
+  - text: wikihow answers texts.
+  - headline: bold lines as summary.
+
+There are two separate versions:
+  - all: consisting of the concatenation of all paragraphs as the articles and
+         the bold lines as the reference summaries.
+  - sep: consisting of each paragraph and its summary.
+
+Download "wikihowAll.csv" and "wikihowSep.csv" from
+https://github.com/mahnazkoupaee/WikiHow-Dataset and place them in manual folder
+https://www.tensorflow.org/datasets/api_docs/python/tfds/download/DownloadConfig.
+Train/validation/test splits are provided by the authors.
+Preprocessing is applied to remove short articles
+(abstract length < 0.75 article length) and clean up extra commas.
+"""
+
+_DOCUMENT = "text"
+_SUMMARY = "headline"
+
+_URLS = {
+    "train": "https://raw.githubusercontent.com/mahnazkoupaee/WikiHow-Dataset/master/all_train.txt",
+    "validation": "https://raw.githubusercontent.com/mahnazkoupaee/WikiHow-Dataset/master/all_val.txt",
+    "test": "https://raw.githubusercontent.com/mahnazkoupaee/WikiHow-Dataset/master/all_test.txt",
+}
+
+
+class WikihowConfig(datasets.BuilderConfig):
+    """BuilderConfig for Wikihow."""
+
+    def __init__(self, filename=None, **kwargs):
+        """BuilderConfig for Wikihow.
+
+        Args:
+          filename: filename of different configs for the dataset.
+          **kwargs: keyword arguments forwarded to super.
+        """
+        # Version 1.1.0 remove empty document and summary strings.
+        # Version 1.2.0 add train validation test split, add cleaning & filtering.
+        super(WikihowConfig, self).__init__(version=datasets.Version("1.2.0"), **kwargs)
+        self.filename = filename
+
+
+class Wikihow(datasets.GeneratorBasedBuilder):
+    """WikiHow: A Large Scale Text Summarization Dataset."""
+
+    BUILDER_CONFIGS = [
+        WikihowConfig(
+            name="all",
+            filename="wikihowAll.csv",
+            description="Use the concatenation of all paragraphs as the articles"
+            " and the bold lines as the reference summaries",
+        ),
+        WikihowConfig(name="sep", filename="wikihowSep.csv", description="use each paragraph and its summary."),
+    ]
+
+    @property
+    def manual_download_instructions(self):
+        return """\
+  You need to manually download two wikihow files. An overview of which files to download can be seen at https://github.com/mahnazkoupaee/WikiHow-Dataset.
+  You need to download the following two files manually:
+    1) https://ucsb.app.box.com/s/ap23l8gafpezf4tq3wapr6u8241zz358 and save the file under <path/to/folder>/wikihowAll.csv
+    2) https://ucsb.app.box.com/s/7yq601ijl1lzvlfu4rjdbbxforzd2oag and save the file under <path/to/folder>/wikihowSep.csv
+
+  The <path/to/folder> can e.g. be "~/manual_wikihow_data".
+
+  Wikihow can then be loaded using the following command `datasets.load_dataset("wikihow", data_dir="<path/to/folder>")`.
+  """
+
+    def _info(self):
+        feature_names = [_DOCUMENT, _SUMMARY, "title"]
+        if self.config.name == "sep":
+            feature_names.extend(["overview", "sectionLabel"])
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features({k: datasets.Value("string") for k in feature_names}),
+            supervised_keys=None,
+            homepage="https://github.com/mahnazkoupaee/WikiHow-Dataset",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        dl_path = dl_manager.download_and_extract(_URLS)
+        titles = {k: set() for k in dl_path}
+        for k, path in dl_path.items():
+            with open(path, encoding="utf-8") as f:
+                for line in f:
+                    titles[k].add(line.strip())
+
+        path_to_manual_file = os.path.join(
+            os.path.abspath(os.path.expanduser(dl_manager.manual_dir)), self.config.filename
+        )
+
+        if not os.path.exists(path_to_manual_file):
+            raise FileNotFoundError(
+                "{} does not exist. Make sure you insert a manual dir via `datasets.load_dataset('wikihow', data_dir=...)` that includes a file name {}. Manual download instructions: {})".format(
+                    path_to_manual_file, self.config.filename, self.manual_download_instructions
+                )
+            )
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "path": path_to_manual_file,
+                    "title_set": titles["train"],
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "path": path_to_manual_file,
+                    "title_set": titles["validation"],
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "path": path_to_manual_file,
+                    "title_set": titles["test"],
+                },
+            ),
+        ]
+
+    def _generate_examples(self, path=None, title_set=None):
+        """Yields examples."""
+        with open(path, encoding="utf-8") as f:
+            reader = csv.reader(f)
+            headers = next(reader)
+            if self.config.name == "all" and headers != ["headline", "title", "text"]:
+                raise ValueError("Mismatched header in WikiAll.txt")
+            if self.config.name == "sep" and headers != ["overview", "headline", "text", "sectionLabel", "title"]:
+                raise ValueError("Mismatched header in WikiSep.txt")
+            key2id = {key: i for i, key in enumerate(headers)}
+            for i, line in enumerate(reader):
+                # skip empty line or insufficient line.
+                if len(line) == len(key2id):
+                    summary = line[key2id[_SUMMARY]].strip()
+                    document = line[key2id[_DOCUMENT]].strip()
+                    summary, document = _filter_and_clean(summary, document)
+                    if summary and document:
+                        if line[key2id["title"]].strip().replace(" ", "") in title_set:
+                            d = {k: line[v].strip() for k, v in key2id.items() if k not in [_SUMMARY, _DOCUMENT]}
+                            d[_DOCUMENT] = document
+                            d[_SUMMARY] = summary
+                            yield i, d
+
+
+# This functions follow data processing acoording to original paper at
+# https://github.com/mahnazkoupaee/WikiHow-Dataset/blob/master/process.py
+def _filter_and_clean(abstract, article):
+    """Remove short article and clean up commas in abstract and article."""
+    # a threshold is used to remove short articles with long summaries
+    # as well as articles with no summary
+    if len(abstract) < (0.75 * len(article)):
+        # remove extra commas in abstracts
+        abstract = abstract.replace(".,", ".")
+        # remove extra commas in articles
+        article = re.sub(r"[.]+[\n]+[,]", ".\n", article)
+        return abstract, article
+    else:
+        return "", ""