Upload _scigen.py

_scigen.py

@@ -0,0 +1,67 @@
+"""Scigen: dataset for reasoning-aware data-to-text generation from scientific tables"""
+
+import json
+import datasets
+import glob
+import os
+
+_CITATION = """\
+@article{moosavi:2021:SciGen,
+  author    = {Nafise Sadat Moosavi, Andreas R{\"u}ckl{\'e}, Dan Roth, Iryna Gurevych},
+  title     = {Learning to Reason for Text Generation from Scientific Tables},
+  journal   = {arXiv preprint arXiv:2104.08296},
+  year      = {2021},
+  url       = {https://arxiv.org/abs/2104.08296}
+}
+"""
+_DESCRIPTION = """\
+SciGen is dataset for the task of reasoning-aware data-to-text generation consisting of tables from scientific articles and their corresponding descriptions.
+"""
+
+_URL = "https://github.com/UKPLab/SciGen"
+_LICENSE = "CC BY-NC-SA 4.0"
+
+class SciGen(datasets.GeneratorBasedBuilder):
+    VERSION = "1.0.0"
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features({
+                'paper': datasets.Value(dtype='string'),
+                'paper_id': datasets.Value(dtype='string'),
+                'table_caption': datasets.Value(dtype='string'),
+                'table_column_names': datasets.Value(dtype='large_string'),
+                'table_content_values': datasets.Value(dtype='large_string'),
+                'text' : datasets.Value(dtype='large_string'),
+            }),
+            supervised_keys=None,
+            homepage=_URL,
+            citation=_CITATION,
+            license=_LICENSE
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": "dataset", "split" : "train"}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": "dataset", "split" : "dev"}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": "dataset", "split" : "test"}),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        data_dir = "development" if split == "dev" else split
+
+        if split in ["train", "dev"]:
+            file_path = os.path.join(filepath, data_dir, "medium", f"{split}.json")
+        else:
+            # there is also "test-Other.json", should be looked into
+            file_path = os.path.join(filepath, data_dir, f"test-CL.json")
+
+        with open(file_path) as f:
+            j = json.load(f)
+            for example_idx, entry in enumerate(list(j.values())):
+                yield example_idx, {key: str(value) for key, value in entry.items()}
+
+if __name__ == '__main__':
+    dataset = datasets.load_dataset(__file__)
+    dataset.push_to_hub("kasnerz/scigen")