add datasets script

KorQuADv1.py

@@ -0,0 +1,103 @@
+import datasets
+import pandas as pd
+
+_DATA_URLS = {
+    "train": "https://korquad.github.io/dataset/KorQuAD_v1.0_train.json",
+    "dev": "https://korquad.github.io/dataset/KorQuAD_v1.0_dev.json",
+}
+_VERSION = "0.0.0"
+_LICENSE = "CC BY-ND 2.0 KR"
+_CITATION = """\
+@misc{lim2019korquad1.0,
+      title={KorQuAD1.0: Korean QA Dataset for Machine Reading Comprehension},
+      author={Seungyoung Lim, Myungji Kim, Jooyoul Lee},
+      year={2019},
+      eprint={1909.07005},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+_HOMEPAGE = "https://korquad.github.io/KorQuad%201.0/"
+_DESCRIPTION = """\
+KorQuAD 1.0 (Korean Question Answering Dataset v1.0)
+KorQuAD 1.0 is a dataset created for Korean Machine Reading Comprehension.
+The answers to all your questions are made up of some subareas in the corresponding Wikipedia article paragraphs.
+It is structured in the same way as the Stanford Question Answering Dataset (SQuAD) v1.0.
+"""
+
+
+class KorQuADV1Config(datasets.BuilderConfig):
+    def __init__(self, data_url, features, **kwargs):
+        super().__init__(version=datasets.Version(_VERSION, ""), **kwargs)
+        self.features = features
+        self.data_url = data_url
+        
+
+class KorQuADV1(datasets.GeneratorBasedBuilder):
+    DEFAULT_CONFIG_NAME = "korquad"
+    BUILDER_CONFIGS = [
+        KorQuADV1Config(
+            name="korquad",
+            data_url=_DATA_URLS,
+            features=datasets.Features(
+                {
+                    "answers": datasets.Sequence(
+                        feature={
+                            "text": datasets.Value(dtype="string"),
+                            "answer_start": datasets.Value(dtype="int32"),
+                        },
+                    ),
+                    "context": datasets.Value(dtype="string"),
+                    "guid": datasets.Value(dtype="string"),
+                    "question": datasets.Value(dtype="string"),
+                    "title": datasets.Value(dtype="string"),
+                }
+            )
+        ),
+    ]
+    
+    def _info(self):
+        return datasets.DatasetInfo(
+            features=self.config.features,
+            description=_DESCRIPTION,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+            license=_LICENSE,
+        )
+    
+    def _split_generators(self, dl_manager):
+        data_path = dl_manager.download(self.config.data_url)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"data_file": data_path["train"]}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"data_file": data_path["dev"]}
+            ),
+        ]
+    
+    def _generate_examples(self, data_file: str):
+        idx = 0
+        korquad = pd.read_json(data_file)
+        for example in korquad["data"].tolist():
+            paragraphs = example["paragraphs"]
+            title = example["title"]
+            for paragraph in paragraphs:
+                qas = paragraph["qas"]
+                context = paragraph["context"]
+                for qa in qas:
+                    text = [answers["text"] for answers in qa["answers"]]
+                    answer_start = [answers["answer_start"] for answers in qa["answers"]]
+                    features = {
+                        "guid": qa["id"],
+                        "question": qa["question"],
+                        "answers": {"text": text, "answer_start": answer_start},
+                        "context": context,
+                        "title": title,
+                    }
+                    yield idx, features
+                    idx += 1