first commit

.gitattributes

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+expanded_ds.json filter=lfs diff=lfs merge=lfs -text
+expanded_ds-dev.json filter=lfs diff=lfs merge=lfs -text
+expanded_ds-train.json filter=lfs diff=lfs merge=lfs -text
+expanded_ds-validation.json filter=lfs diff=lfs merge=lfs -text

deepage2_qa_dataset.py

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+"""TODO: DATASET SHORT DESCRIPTION"""
+
+import json
+import datasets
+from datasets.tasks import TextClassification
+
+_DESCRIPTION = """TODO: DATASET DESCRIPTION"""
+
+_CITATION = """TODO: CITATIONS"""
+
+_URL = "https://huggingface.co/datasets/rsgrava/deepage2_qa_dataset/resolve/main/"
+_URLS = {
+    "train": _URL + "expanded_ds-train.json",
+    "dev": _URL + "expanded_ds-test.json",
+}
+
+class SquadV1PtBr(datasets.GeneratorBasedBuilder):
+    """TODO: SHORT DATASET DESCRIPTION"""
+
+    VERSION = datasets.Version("1.1.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "source_text": datasets.Value("string"),
+                    "target_text": datasets.Value("string"),
+                }
+            ),
+            # No default supervised_keys (as we have to pass both question and context as input).
+            supervised_keys=None,
+            homepage="TODO: HOMEPAGE",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls_to_download = _URLS
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
+        ]
+
+    def _generate_examples(self, filepath):
+        with open(filepath) as f:
+            key = 0
+            ids = []
+            squad = json.load(f)
+            for article in squad["data"]:
+                for paragraph in article["paragraphs"]:
+                    source_text = paragraph["context"].strip()
+                    questions = []
+                    for qa in paragraph["qas"]:
+                        id_ = qa["id"]
+                        if id_ in ids:
+                            #skip duplicate entries
+                            continue
+                        else:
+                            ids.append(id_)
+                        questions.append(qa["question"].strip())
+                    target_text = "<sep>".join(questions)
+
+                    yield key, {
+                        "source_text": source_text,
+                        "target_text": target_text,
+                    }
+                    key += 1

expanded_ds-dev.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:cff81e597d24726e61167b81aef2f608c817138bc44cf20d97b9d29ecd0aa764
+size 276756

expanded_ds-train.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:176ee5873fa73d35465c8b186b3e96320d9b34d1575915553f4397d30a09fe87
+size 1296533

expanded_ds-validation.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c81a2baf95dd66bf22a7853636511ec05b4e8e570d18290ceaf01a55d4c6dae1
+size 276270