Added data loader script - xsum

xsum.py

@@ -0,0 +1,119 @@
+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 = """\
+This is the XSUM subset of the GEM benchmark.
+"""
+_URLs = {
+	"xsum": {
+            "data": "http://bollin.inf.ed.ac.uk/public/direct/XSUM-EMNLP18-Summary-Data-Original.tar.gz",
+            "splits": "https://storage.googleapis.com/huggingface-nlp/datasets/gem/gem_xsum_confidence_0.8.json",
+            "challenge_set": "https://storage.googleapis.com/huggingface-nlp/datasets/gem/gem_challenge_sets/xsum.zip",
+    	},
+    }
+
+_XSUM_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):
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name=lang,
+            version=datasets.Version("1.0.0"),
+            description="",
+        )
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+       	    features = datasets.Features(
+                {
+                    "gem_id": datasets.Value("string"),
+                    "gem_parent_id": datasets.Value("string"),
+                    "xsum_id": datasets.Value("string"),
+                    "document": datasets.Value("string"),
+                    "target": datasets.Value("string"),
+                    "references": [datasets.Value("string")],
+                }     
+	    ),
+            supervised_keys=None,
+            homepage="",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        dl_dir = dl_manager.download_and_extract(_URLs[self.config.name])
+        challenge_sets = [
+            ("challenge_train_sample", "train_xsum_RandomSample500.json"),
+            ("challenge_validation_sample", "validation_xsum_RandomSample500.json"),
+            ("challenge_test_backtranslation", "test_xsum_BackTranslation500.json"),
+            ("challenge_test_bfp_02", "test_xsum_ButterFingersPerturbation_p=0.02_500.json"),
+            ("challenge_test_bfp_05", "test_xsum_ButterFingersPerturbation_p=0.05_500.json"),
+            ("challenge_test_nopunc", "test_xsum_WithoutPunctuation500.json"),
+            ("challenge_test_covid", f"en_test_covid19.jsonl"),  	    
+        ]
+        return [
+            datasets.SplitGenerator(
+                name=challenge_split,
+                gen_kwargs={
+                    "filepath": os.path.join(dl_dir["challenge_set"], "xsum", filename),
+                    "split": challenge_split,
+                },
+            )
+            for challenge_split, filename in challenge_sets 	
+        ]
+
+    def _generate_examples(self, filepath, split, filepaths=None, lang=None):
+        """Yields examples."""
+	if "challenge" in split:
+            if "covid" in split:
+                with open(filepath, encoding="utf-8") as f:
+                    id_ = -1
+                    for line in f:
+                        data = json.loads(line)
+                        id_ += 1
+                        yield id_, {
+                            "gem_id": f"{self.config.name}-{split}-{id_}",
+                            "gem_parent_id": f"{self.config.name}-{split}-{id_}",
+                            "xsum_id": data["url"],
+                            "document": data["text"],
+                            "target": data["summary"],
+                            "references": [] if split == "train" else [data["summary"]],
+                        }
+            else:
+                exples = json.load(open(filepath, encoding="utf-8"))
+                if isinstance(exples, dict):
+                    assert len(exples) == 1, "multiple entries found"
+                    exples = list(exples.values())[0]
+                for id_, exple in enumerate(exples):
+                    exple["gem_parent_id"] = exple["gem_id"]
+                    exple["gem_id"] = f"{self.config.name}-{split}-{id_}"
+                    yield id_, exple