Create FarsTail.py

FarsTail.py

@@ -0,0 +1,76 @@
+import json
+import csv
+import datasets
+_CITATION = """\\
+@article{amirkhani2020farstail,
+  title={FarsTail: A Persian Natural Language Inference Dataset},
+  author={Hossein Amirkhani, Mohammad Azari Jafari, Azadeh Amirak, Zohreh Pourjafari, Soroush Faridan Jahromi, and Zeinab Kouhkan},
+  journal={arXiv preprint arXiv:2009.08820},
+  year={2020}
+}
+"""
+_DESCRIPTION = """\\\\\\\\
+A Persian Natural Language Inference Dataset
+"""
+
+_URL = "https://raw.githubusercontent.com/dml-qom/FarsTail/master/data/"
+_URLS = {
+    "train": _URL + "Train-word.csv",
+    "test": _URL + "Test-word.csv",
+    "validation": _URL + "Val-word.csv"
+}
+class FarsTailConfig(datasets.BuilderConfig):
+    """BuilderConfig for FarsTail."""
+    def __init__(self, **kwargs):
+        """BuilderConfig for FarsTail.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(FarsTailConfig, self).__init__(**kwargs)
+        
+class FarsTail(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        FarsTailConfig(name="FarsTail", version=datasets.Version("1.0.0"), description="persian NLI dataset"),
+    ]
+    def _info(self):
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # datasets.features.FeatureConnectors
+            features=datasets.Features(
+                {
+                    "premise": datasets.Value("string"),
+                    "hypothesis": datasets.Value("string"),
+                    "label": datasets.Value("string")
+                }
+            ),
+            supervised_keys=None,
+            # Homepage of the dataset for documentation
+            homepage="https://github.com/dml-qom/FarsTail",
+            citation=_CITATION,
+        )
+        
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        # dl_manager is a datasets.download.DownloadManager that can be used to
+        # download and extract URLs
+        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.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["validation"]}),
+        ]
+
+    def _generate_examples(self, filepath):
+        try:
+            with open(filepath, encoding="utf-8") as f:
+                reader = csv.DictReader(f, delimiter="\t")
+                for idx, row in enumerate(reader):
+                    yield idx, {
+                        "premise": row["premise"],
+                        "hypothesis": row["hypothesis"],
+                        "label": row["label"],
+                    }
+        except Exception as e:
+            print(e)