Upload ai_hub_summarization.py

ai_hub_summarization.py

@@ -0,0 +1,78 @@
+import csv
+import datasets
+
+_CITATION = """"""
+_DESCRIPTION = """"""
+_LICENSE = "CC-BY-SA-4.0"
+# _URL = "https://github.com/boostcampaitech2/data-annotation-nlp-level3-nlp-14"
+_DATA_URLS = {
+    "train": "https://huggingface.co/datasets/raki-1203/ai_hub_summarization/resolve/main/train_abstract_summary_v1.0.json",
+    "dev": "https://huggingface.co/datasets/raki-1203/ai_hub_summarization/resolve/main/train_abstract_summary_v1.0.json",
+}
+
+_VERSION = "0.0.0"
+
+
+class AiHubSummarizationConfig(datasets.BuilderConfig):
+    def __init__(self, data_url, **kwargs):
+        super().__init__(version=datasets.Version(_VERSION), **kwargs)
+        self.data_url = data_url
+
+
+class AiHubSummarization(datasets.GeneratorBasedBuilder):
+    DEFAULT_CONFIG_NAME = "pred"
+    BUILDER_CONFIGS = [
+        AiHubSummarizationConfig(
+            name="ai_hub_summarization",
+            data_url=_DATA_URLS,
+            description=_DESCRIPTION,
+        )
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "passage": datasets.Value("string"),
+                    "abstract_summary": datasets.Value("string"),
+                }
+            ),
+            license=_LICENSE,
+            citation=_CITATION,
+            supervised_keys=None,
+        )
+
+    def _split_generators(self, dl_manager):
+        """ Returns SplitGenerators. """
+        data_file = dl_manager.download_and_extract(self.config.data_url)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "data_file": data_file["train"],
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "data_file": data_file["dev"],
+                    "split": "valid",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, data_file: str, split: str):
+        """ Yields examples. """
+        with open(data_file, newline='', encoding="UTF-8") as csvfile:
+            reader = csv.reader(csvfile, delimiter=',')
+            feature_names = next(reader)
+            idx = 0
+            for row in reader:
+                features = {
+                    "passage": row[0],
+                    "abstract_summary": row[1],
+                }
+                yield idx, features
+                idx += 1