Create quad2.py

quad2.py

@@ -0,0 +1,92 @@
+"""UnibQuAD: A Indonesian-Language Question Answering Dataset Base On University Of Bengkulu."""
+
+import json
+
+import datasets
+
+
+logger = datasets.logging.get_logger(__name__)
+
+
+_CITATION = """  """
+
+_DESCRIPTION = """  """
+
+_URL = "https://drive.google.com/uc?export=download&id=1rL3i2ePYM-yVpdCbYQR67wrcgHytqzy8"
+
+
+class UnibQuADConfig(datasets.BuilderConfig):
+    """BuilderConfig for UnibQuAD."""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for UnibQuAD.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(UnibQuADConfig, self).__init__(**kwargs)
+
+
+class UnibDPR(datasets.GeneratorBasedBuilder):
+    """UnibQuAD: A Indonesian-Language Question Answering Dataset Base On University Of Bengkulu."""
+
+    BUILDER_CONFIGS = [
+        UnibQuADConfig(
+            name="plain_text",
+            version=datasets.Version("1.0.0", ""),
+            description="Plain text",
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "context": datasets.Value("string"),
+                    "question": datasets.Value("string"),
+                    "answers": datasets.features.Sequence(
+                        {
+                            "text": datasets.Value("string"),                            
+                            "answer_start": datasets.Value("int32"),
+                        }
+                    )
+                }
+            ),
+            # No default supervised_keys (as we have to pass both question
+            # and context as input).
+            supervised_keys=None,
+            homepage=" ",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        downloaded_files = dl_manager.download_and_extract(_URL)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files+"/quad2/train_quad2.json"}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files+"/quad2/test_quad2.json"}),
+        ]
+
+    def _generate_examples(self, filepath):
+        """This function returns the examples in the raw (text) form."""
+        logger.info("generating examples from = %s", filepath)
+        with open(filepath, encoding="utf-8") as f:
+            UnibQuAD = json.load(f)
+            for article in UnibQuAD["data"]:
+                for paragraph in article["paragraphs"]:
+                    context = paragraph["context"]
+                    document_id = paragraph["document_id"]
+                    for qa in paragraph["qas"]:
+                        question = qa["question"]
+                        id_ = qa["id"]
+                        answers = [{"answer_start": answer["answer_start"], "text": answer["text"]} for answer in qa["answers"]]
+
+                        # Features currently used are "context", "question", and "answers".
+                        # Others are extracted here for the ease of future expansions.
+                        yield id_, {
+                            "context": context,
+                            "question": question,
+                            "id": id_,
+                            "answers": answers,
+                        }