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mediasum.py

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+import json
+import os
+
+import datasets
+from datasets.tasks import TextClassification
+
+_CITATION = None
+
+
+_DESCRIPTION = """
+ MediaSum dataset for summarization.
+ From paper: "MediaSum: A Large-scale Media Interview Dataset for Dialogue Summarization" by C. Zhu et al."
+
+"""
+_CITATION = """\
+    @article{zhu2021mediasum,
+  title={MediaSum: A Large-scale Media Interview Dataset for Dialogue Summarization},
+  author={Zhu, Chenguang and Liu, Yang and Mei, Jie and Zeng, Michael},
+  journal={arXiv preprint arXiv:2103.06410},
+  year={2021}
+}
+"""
+_ABSTRACT = "summary"
+_ARTICLE = "utt"
+
+class MediaSumSummarizationConfig(datasets.BuilderConfig):
+    """BuilderConfig for MediaSumSummarization."""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for MediaSumSummarization.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(MediaSumSummarizationConfig, self).__init__(**kwargs)
+
+
+class MediaSumSummarizationDataset(datasets.GeneratorBasedBuilder):
+    """MediaSumSummarization Dataset."""
+    
+    _TRAIN_FILE = "train_data.zip"
+    _VAL_FILE = "val_data.zip"
+    _TEST_FILE = "test_data.zip"
+
+    BUILDER_CONFIGS = [
+        MediaSumSummarizationConfig(
+            name="newline",
+            version=datasets.Version("1.0.0"),
+            description="MediaSum dataset for summarization, concat sections",
+        ),
+        MediaSumSummarizationConfig(
+            name="roberta",
+            version=datasets.Version("1.0.0"),
+            description="MediaSum dataset for summarization, document",
+        ),
+        MediaSumSummarizationConfig(
+            name="bert",
+            version=datasets.Version("1.0.0"),
+            description="MediaSum dataset for summarization, document",
+        ),
+        MediaSumSummarizationConfig(
+            name="list",
+            version=datasets.Version("1.0.0"),
+            description="MediaSum dataset for summarization, document",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "roberta"
+
+    def _info(self):
+        # Should return a datasets.DatasetInfo object
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    _ARTICLE: datasets.Sequence(datasets.Value("string")) if self.config.name == "list" else datasets.Value("string"),
+                    _ABSTRACT: datasets.Value("string"),
+                    #"id": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+            homepage="https://github.com/zcgzcgzcg1/MediaSum",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+
+        train_path = dl_manager.download_and_extract(self._TRAIN_FILE) + "/train_data.txt"
+        val_path = dl_manager.download_and_extract(self._VAL_FILE) + "/val_data.txt"
+        test_path = dl_manager.download_and_extract(self._TEST_FILE) + "/test_data.txt"
+        
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION, gen_kwargs={"filepath": val_path}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST, gen_kwargs={"filepath": test_path}
+            ),
+        ]
+    
+    def _generate_examples(self, filepath):
+        """Generate MediaSumSummarization examples."""
+        if self.config.name == "newline":
+            join_ = "\n"
+        elif self.config.name == "roberta":
+            join_ = "</s>"
+        elif self.config.name == "bert": 
+            join_ = "[SEP]"
+
+        with open(filepath, encoding="utf-8") as f:
+            for id_, row in enumerate(f):
+                data = json.loads(row)
+
+                """
+                'summary': str,
+                'document': List[str],
+                """
+                document = data["utt"]
+                if self.config.name != "list":
+                    document = join_.join(document)
+                summary = data["summary"]
+                yield id_, {"document": document, "summary": summary}