Convert dataset to Parquet

README.md

@@ -19,19 +19,6 @@ task_categories:
 - summarization
 task_ids:
 - news-articles-summarization
-train-eval-index:
-- config: default
-  task: summarization
-  task_id: summarization
-  splits:
-    train_split: train
-    eval_split: test
-  col_mapping:
-    document: text
-    summary: target
-  metrics:
-  - type: rouge
-    name: Rouge
 dataset_info:
   features:
   - name: document
@@ -42,16 +29,38 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 479206608
+    num_bytes: 479206363
     num_examples: 204045
   - name: validation
-    num_bytes: 26292901
+    num_bytes: 26292877
     num_examples: 11332
   - name: test
-    num_bytes: 26756165
+    num_bytes: 26756141
     num_examples: 11334
-  download_size: 257302866
-  dataset_size: 532255674
+  download_size: 332791351
+  dataset_size: 532255381
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: validation
+    path: data/validation-*
+  - split: test
+    path: data/test-*
+train-eval-index:
+- config: default
+  task: summarization
+  task_id: summarization
+  splits:
+    train_split: train
+    eval_split: test
+  col_mapping:
+    document: text
+    summary: target
+  metrics:
+  - type: rouge
+    name: Rouge
 ---
 
 # Dataset Card for "xsum"

data/{XSUM-EMNLP18-Summary-Data-Original.tar.gz → test-00000-of-00001.parquet}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:10b48aa187fc9c904b30f76ca97e2da0de8d3a1238acc26acadef93e2001af90
-size 254582292
+oid sha256:224e9dbc6fed987759c1954603b43cb280b8d475d78893779130aa707d967ed7
+size 16731226

data/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0bba72d330f2a35ba20321444e54724e487b49f2eab6b26625b5f282d1c797c9
+size 299612457

data/validation-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b7fc808c2dd3d1340349481aeef489e6eb8c22ff5739d8bce6d0f99e5ef8044d
+size 16447668

xsum.py

@@ -1,170 +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
-"""XSum dataset."""
-
-
-import json
-import os
-
-import datasets
-
-
-_CITATION = """
-@article{Narayan2018DontGM,
-  title={Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization},
-  author={Shashi Narayan and Shay B. Cohen and Mirella Lapata},
-  journal={ArXiv},
-  year={2018},
-  volume={abs/1808.08745}
-}
-"""
-
-_DESCRIPTION = """
-Extreme Summarization (XSum) Dataset.
-
-There are three features:
-  - document: Input news article.
-  - summary: One sentence summary of the article.
-  - id: BBC ID of the article.
-
-"""
-
-# From https://github.com/EdinburghNLP/XSum/issues/12
-_URL_DATA = "data/XSUM-EMNLP18-Summary-Data-Original.tar.gz"
-_URL_SPLITS = (
-    "https://raw.githubusercontent.com/EdinburghNLP/XSum/master/XSum-Dataset/XSum-TRAINING-DEV-TEST-SPLIT-90-5-5.json"
-)
-
-_DOCUMENT = "document"
-_SUMMARY = "summary"
-_ID = "id"
-
-_REMOVE_LINES = set(
-    [
-        "Share this with\n",
-        "Email\n",
-        "Facebook\n",
-        "Messenger\n",
-        "Twitter\n",
-        "Pinterest\n",
-        "WhatsApp\n",
-        "Linkedin\n",
-        "LinkedIn\n",
-        "Copy this link\n",
-        "These are external links and will open in a new window\n",
-    ]
-)
-
-
-class Xsum(datasets.GeneratorBasedBuilder):
-    """Extreme Summarization (XSum) Dataset."""
-
-    # Version 1.2.0 expands coverage, includes ids, and removes web contents.
-    VERSION = datasets.Version("1.2.0")
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    _DOCUMENT: datasets.Value("string"),
-                    _SUMMARY: datasets.Value("string"),
-                    _ID: datasets.Value("string"),
-                }
-            ),
-            supervised_keys=(_DOCUMENT, _SUMMARY),
-            homepage="https://github.com/EdinburghNLP/XSum/tree/master/XSum-Dataset",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-
-        files_to_download = {"data": _URL_DATA, "splits": _URL_SPLITS}
-        downloaded_files = dl_manager.download(files_to_download)
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "split_path": downloaded_files["splits"],
-                    "split_name": "train",
-                    "data_dir": "bbc-summary-data",
-                    "files": dl_manager.iter_archive(downloaded_files["data"]),
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "split_path": downloaded_files["splits"],
-                    "split_name": "validation",
-                    "data_dir": "bbc-summary-data",
-                    "files": dl_manager.iter_archive(downloaded_files["data"]),
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "split_path": downloaded_files["splits"],
-                    "split_name": "test",
-                    "data_dir": "bbc-summary-data",
-                    "files": dl_manager.iter_archive(downloaded_files["data"]),
-                },
-            ),
-        ]
-
-    def _generate_examples(self, split_path, split_name, data_dir, files):
-        """Yields examples."""
-
-        with open(split_path, "r", encoding="utf-8") as f:
-            split_ids = json.load(f)
-        split_ids = {k: set(v) for k, v in split_ids.items()}
-
-        for path, f in files:
-            if not split_ids[split_name]:
-                break
-            elif path.startswith(data_dir) and path.endswith(".summary"):
-                i = os.path.basename(path).split(".")[0]
-                if i in split_ids[split_name]:
-                    split_ids[split_name].remove(i)
-                    text = "".join(
-                        [
-                            line.decode("utf-8")
-                            for line in f.readlines()
-                            if line.decode("utf-8") not in _REMOVE_LINES and line.strip()
-                        ]
-                    )
-                    # Each file follows below format:
-                    # [SN]URL[SN]
-                    # http://somelink
-                    #
-                    # [SN]TITLE[SN]
-                    # some intro
-                    #
-                    # [SN]FIRST-SENTENCE[SN]
-                    # some intro
-                    #
-                    # [SN]RESTBODY[SN]
-                    # text line.
-                    # another text line.
-                    # "another text line."
-
-                    # According to the following issue, FIRST-SENTENCE
-                    # is the reference summary and TITLE is unused:
-                    # https://github.com/EdinburghNLP/XSum/issues/22
-                    segs = text.split("[SN]")
-                    yield i, {_DOCUMENT: segs[8].strip(), _SUMMARY: segs[6].strip(), _ID: i}