multi_news dataset

multi_news.py

@@ -0,0 +1,105 @@
+# 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
+"""Multi-News dataset."""
+
+
+import os
+
+import datasets
+
+
+_CITATION = """
+@misc{alex2019multinews,
+    title={Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model},
+    author={Alexander R. Fabbri and Irene Li and Tianwei She and Suyi Li and Dragomir R. Radev},
+    year={2019},
+    eprint={1906.01749},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """
+Multi-News, consists of news articles and human-written summaries
+of these articles from the site newser.com.
+Each summary is professionally written by editors and
+includes links to the original articles cited.
+
+There are two features:
+  - document: text of news articles seperated by special token "|||||".
+  - summary: news summary.
+"""
+
+_URL = "https://drive.google.com/uc?export=download&id=1vRY2wM6rlOZrf9exGTm5pXj5ExlVwJ0C"
+
+_DOCUMENT = "document"
+_SUMMARY = "summary"
+
+
+class MultiNews(datasets.GeneratorBasedBuilder):
+    """Multi-News dataset."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features({_DOCUMENT: datasets.Value("string"), _SUMMARY: datasets.Value("string")}),
+            supervised_keys=(_DOCUMENT, _SUMMARY),
+            homepage="https://github.com/Alex-Fabbri/Multi-News",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        extract_path = os.path.join(dl_manager.download_and_extract(_URL), "multi-news-original")
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"path": os.path.join(extract_path, "train")},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"path": os.path.join(extract_path, "val")},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"path": os.path.join(extract_path, "test")},
+            ),
+        ]
+
+    def _generate_examples(self, path=None):
+        """Yields examples."""
+        with open(os.path.join(path + ".src"), encoding="utf-8") as src_f, open(
+            os.path.join(path + ".tgt"), encoding="utf-8"
+        ) as tgt_f:
+            for i, (src_line, tgt_line) in enumerate(zip(src_f, tgt_f)):
+                yield i, {
+                    # In original file, each line has one example and natural newline
+                    # tokens "\n" are being replaced with "NEWLINE_CHAR". Here restore
+                    # the natural newline token to avoid special vocab "NEWLINE_CHAR".
+                    _DOCUMENT: src_line.strip().replace("NEWLINE_CHAR", "\n"),
+                    # Remove the starting token "- " for every target sequence.
+                    _SUMMARY: tgt_line.strip().lstrip("- "),
+                }
+
+
+if __name__ == '__main__':
+    from datasets import load_dataset
+
+    ssfd_debug = load_dataset("multi_news.py")
+    x = 5