Create parsinlu-multiple-choice.py

parsinlu-multiple-choice.py

@@ -0,0 +1,118 @@
+"""ParsiNLU Persian multiple choice task (Mostly copy-paste from https://huggingface.co/datasets/persiannlp/parsinlu_reading_comprehension/blob/main/parsinlu_reading_comprehension.py)"""
+
+
+from __future__ import absolute_import, division, print_function
+
+import json
+
+import datasets
+
+
+logger = datasets.logging.get_logger(__name__)
+
+_CITATION = """\
+@article{huggingface:dataset,
+    title = {ParsiNLU: A Suite of Language Understanding Challenges for Persian},
+    authors = {Khashabi, Daniel and Cohan, Arman and Shakeri, Siamak and Hosseini, Pedram and Pezeshkpour, Pouya and Alikhani, Malihe and Aminnaseri, Moin and Bitaab, Marzieh and Brahman, Faeze and Ghazarian, Sarik and others},
+    year={2020}
+    journal = {arXiv e-prints},
+    eprint = {2012.06154},    
+}
+"""
+
+# You can copy an official description
+_DESCRIPTION = """A Persian multiple choice task."""
+
+_HOMEPAGE = "https://github.com/persiannlp/parsinlu/"
+
+_LICENSE = "CC BY-NC-SA 4.0"
+
+_URL = "https://raw.githubusercontent.com/persiannlp/parsinlu/master/data/multiple_choice/"
+_URLs = {
+    "train": _URL + "train.jsonl",
+    "val": _URL + "valid.jsonl",
+    "test": _URL + "test.jsonl",
+}
+
+
+class ParsinluMultipleChoice(datasets.GeneratorBasedBuilder):
+    """ParsiNLU Persian multiple choice task."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="parsinlu-repo", version=VERSION, description="ParsiNLU repository: multiple choice"
+        ),
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "answer": datasets.Value("int64"),
+                "candidates": datasets.features.Sequence(feature=Value(dtype='string', id=None), length=-1),
+                "category": datasets.Value("string"),
+                "question": datasets.Value("string"),
+                "id": datasets.Value("string")
+            }
+        )
+
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # This defines the different columns of the dataset and their types
+            features=features,  # Here we define them above because they are different between the two configurations
+            # If there's a common (input, target) tuple from the features,
+            # specify them here. They'll be used if as_supervised=True in
+            # builder.as_dataset.
+            supervised_keys=None,
+            # Homepage of the dataset for documentation
+            homepage=_HOMEPAGE,
+            # License for the dataset if available
+            license=_LICENSE,
+            # Citation for the dataset
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        data_dir = dl_manager.download_and_extract(_URLs)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": data_dir["train"],
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"filepath": data_dir["test"], "split": "test"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": data_dir["val"],
+                    "split": "validation",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        logger.info("generating examples from = %s", filepath)
+
+        def get_answer_index(passage, answer):
+            return passage.index(answer) if answer in passage else -1
+
+        with open(filepath, encoding="utf-8") as f:
+            for id_, row in enumerate(f):
+                data = json.loads(row)
+                yield id_, {
+                    "answer": data["question"],
+                    "candidates": data["candidates"],
+                    "category": data["category"],
+                    "question": data["question"],
+                    "id": data['id']
+                }