update

qg_dequad.py

@@ -0,0 +1,65 @@
+""" python -c "from datasets import load_dataset;load_dataset('.')" """
+import json
+from itertools import chain
+import datasets
+
+logger = datasets.logging.get_logger(__name__)
+_DESCRIPTION = """[GermanSQuAD](https://huggingface.co/datasets/deepset/germanquad) dataset for question generation (QG) task."""
+_URL = 'https://huggingface.co/datasets/asahi417/qg_dequad/raw/main/data/processed'
+_URLS = {
+    str(datasets.Split.TEST): [f'{_URL}/test{i:02d}.jsonl' for i in range(5)],
+    str(datasets.Split.TRAIN): [f'{_URL}/train{i:02d}.jsonl' for i in range(19)],
+    str(datasets.Split.VALIDATION): [f'{_URL}/validation{i:02d}.jsonl' for i in range(5)],
+}
+
+
+class QGDEQuADConfig(datasets.BuilderConfig):
+    """BuilderConfig for SquadQG"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for SquadQG.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(QGDEQuADConfig, self).__init__(**kwargs)
+
+
+class QGDEQuAD(datasets.GeneratorBasedBuilder):
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "answer": datasets.Value("string"),
+                    "question": datasets.Value("string"),
+                    "sentence": datasets.Value("string"),
+                    "paragraph": datasets.Value("string"),
+                    "sentence_answer": datasets.Value("string"),
+                    "paragraph_answer": datasets.Value("string"),
+                    "paragraph_sentence": datasets.Value("string"),
+                    "paragraph_id": datasets.Value("string")
+                }
+            ),
+            supervised_keys=None,
+            homepage="https://github.com/asahi417/lm-question-generation"
+        )
+
+    def _split_generators(self, dl_manager):
+        downloaded_file = dl_manager.download_and_extract(_URLS)
+        return [datasets.SplitGenerator(name=i, gen_kwargs={"filepaths": downloaded_file[str(i)]})
+                for i in [datasets.Split.TRAIN, datasets.Split.VALIDATION, datasets.Split.TEST]]
+
+    def _generate_examples(self, filepaths):
+        _key = 0
+        for filepath in filepaths:
+            logger.info("generating examples from = %s", filepath)
+            with open(filepath, encoding="utf-8") as f:
+                _list = f.read().split('\n')
+                if _list[-1] == '':
+                    _list = _list[:-1]
+                for i in _list:
+                    data = json.loads(i)
+                    yield _key, data
+                    _key += 1
+