Upload xsum-kk3.py

xsum-kk3.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
+"""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/data1.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": "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": "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": "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(".summarykz"):
+                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]")
+                    #print(segs[8].strip())
+                    yield i, {_DOCUMENT: segs[8].strip(), _SUMMARY: segs[6].strip(), _ID: i}