Create crosssum.py

crosssum.py

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+"""CrossSum cross-lingual abstractive summarization dataset."""
+
+
+import json
+import os
+
+import datasets
+
+
+_CITATION = """\
+@article{hasan2021crosssum,
+  author    = {Tahmid Hasan and Abhik Bhattacharjee and Wasi Uddin Ahmad and Yuan-Fang Li and Yong-bin Kang and Rifat Shahriyar},
+  title     = {CrossSum: Beyond English-Centric Cross-Lingual Abstractive Text Summarization for 1500+ Language Pairs},
+  journal   = {CoRR},
+  volume    = {abs/2112.08804},
+  year      = {2021},
+  url       = {https://arxiv.org/abs/2112.08804},
+  eprinttype = {arXiv},
+  eprint    = {2112.08804}
+}
+"""
+
+
+_DESCRIPTION = """\
+We present CrossSum, a large-scale dataset
+comprising 1.70 million cross-lingual article summary samples in 1500+ language-pairs
+constituting 45 languages. We use the multilingual XL-Sum dataset and align identical 
+articles written in different languages via crosslingual retrieval using a language-agnostic 
+representation model. 
+"""
+
+_HOMEPAGE = "https://github.com/csebuetnlp/CrossSum"
+
+_LICENSE = "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)"
+
+_URL = "https://huggingface.co/datasets/csebuetnlp/CrossSum/resolve/main/data/{}-{}_CrossSum.tar.bz2"
+
+_LANGUAGES = [
+    "oromo",
+    "french",
+    "amharic",
+    "arabic",
+    "azerbaijani",
+    "bengali",
+    "burmese",
+    "chinese_simplified",
+    "chinese_traditional",
+    "welsh",
+    "english",
+    "kirundi",
+    "gujarati",
+    "hausa",
+    "hindi",
+    "igbo",
+    "indonesian",
+    "japanese",
+    "korean",
+    "kyrgyz",
+    "marathi",
+    "spanish",
+    "scottish_gaelic",
+    "nepali",
+    "pashto",
+    "persian",
+    "pidgin",
+    "portuguese",
+    "punjabi",
+    "russian",
+    "serbian_cyrillic",
+    "serbian_latin",
+    "sinhala",
+    "somali",
+    "swahili",
+    "tamil",
+    "telugu",
+    "thai",
+    "tigrinya",
+    "turkish",
+    "ukrainian",
+    "urdu",
+    "uzbek",
+    "vietnamese",
+    "yoruba",
+]
+
+
+class Crosssum(datasets.GeneratorBasedBuilder):
+    
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="{}-{}".format(src_lang, tgt_lang),
+            version=datasets.Version("1.0.0")
+        )
+        for src_lang in _LANGUAGES 
+        for tgt_lang in _LANGUAGES
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "source_url": datasets.Value("string"),
+                    "target_url": datasets.Value("string"),
+                    "summary": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+            license=_LICENSE,
+            version=self.VERSION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        lang = str(self.config.name)
+        url = _URL.format(lang, self.VERSION.version_str[:-2])
+
+        data_dir = dl_manager.download_and_extract(url)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, lang + "_train.jsonl"),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, lang + "_test.jsonl"),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, lang + "_val.jsonl"),
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """Yields examples as (key, example) tuples."""
+        with open(filepath, encoding="utf-8") as f:
+            for idx_, row in enumerate(f):
+                data = json.loads(row)
+                yield idx_, {
+                    "source_url": data["source_url"],
+                    "target_url": data["target_url"],
+                    "summary": data["summary"],
+                    "text": data["text"],
+                }