Initial commit

MiniLongBench.py

@@ -0,0 +1,113 @@
+import os
+
+import datasets
+import json
+
+
+_DESCRIPTION = """empty"""
+
+_HOMEPAGE = "empty"
+
+_URL = r"https://hf-mirror.com/datasets/linggm/MiniLongBench/resolve/main/data.zip"
+
+
+task_list = [
+    "narrativeqa",
+    "qasper",
+    "multifieldqa_en",
+    "multifieldqa_zh",
+    "hotpotqa",
+    "2wikimqa",
+    "musique",
+    "dureader",
+    "gov_report",
+    "qmsum",
+    "multi_news",
+    "vcsum",
+    "trec",
+    "triviaqa",
+    "samsum",
+    "lsht",
+    "passage_count",
+    "passage_retrieval_en",
+    "passage_retrieval_zh",
+    "lcc",
+    "repobench-p",
+    "qasper_e",
+    "multifieldqa_en_e",
+    "hotpotqa_e",
+    "2wikimqa_e",
+    "gov_report_e",
+    "multi_news_e",
+    "trec_e",
+    "triviaqa_e",
+    "samsum_e",
+    "passage_count_e",
+    "passage_retrieval_en_e",
+    "lcc_e",
+    "repobench-p_e"
+]
+
+
+class MiniLongBenchConfig(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        super().__init__(version=datasets.Version("1.0.0"), **kwargs)
+
+
+class MiniLongBench(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        MiniLongBenchConfig(
+            name=task_name,
+        )
+        for task_name in task_list
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "input": datasets.Value("string"), 
+                "context": datasets.Value("string"), 
+                "answers": [datasets.Value("string")], 
+                "length": datasets.Value("int32"), 
+                "dataset": datasets.Value("string"), 
+                "language": datasets.Value("string"), 
+                "all_classes": [datasets.Value("string")],
+                "_id": datasets.Value("string"), 
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+        )
+
+    def _split_generators(self, dl_manager):
+        #data_dir = dl_manager.download_and_extract(_URL)
+        data_dir = 'YOUR_LOCAL_DIR'
+        task_name = self.config.name
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": os.path.join(
+                        data_dir, "data", f"{task_name}.jsonl"
+                    ),
+                },
+            )
+        ]
+
+    def _generate_examples(self, filepath):
+        with open(filepath, encoding="utf-8") as f:
+            for idx, line in enumerate(f):
+                key = f"{self.config.name}-{idx}"
+                item = json.loads(line)
+                yield key, {
+                    "input": item["input"],
+                    "context": item["context"],
+                    "answers": item["answers"],
+                    "length": item["length"],
+                    "dataset": item["dataset"],
+                    "language": item["language"],
+                    "_id": item["_id"],
+                    "all_classes": item["all_classes"],
+                }