Upload abusive_clauses_loader.py

abusive_clauses_loader.py

@@ -0,0 +1,75 @@
+from pathlib import Path
+
+import datasets
+import pandas as pd
+
+_CITATION = """\
+@InProceedings{AbusiveClauses:dataset,
+title = {AbusiveClauses},
+author={},
+year={2022}
+}
+"""
+
+_DESCRIPTION = "Binary Abusive Clauses in Polish"
+
+_HOMEPAGE = ""
+_LICENSE = ""
+_LABELS = ["KLAUZULA_ABUZYWNA", "BEZPIECZNE_POSTANOWIENIE_UMOWNE"]
+
+DATA_PATH = Path(".")
+
+
+class AbusiveClausesConfig(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        super(AbusiveClausesConfig, self).__init__(**kwargs)
+
+
+class AbusiveClausesDataset(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    TRAIN_FILE = DATA_PATH / "train.csv"
+    VAL_FILE = DATA_PATH / "dev.csv"
+    TEST_FILE = DATA_PATH / "test.csv"
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="abusive-clauses-pl", version=VERSION)
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "text": datasets.Value("string"),
+                "label": datasets.features.ClassLabel(
+                    names=_LABELS, num_classes=len(_LABELS)
+                ),
+            }
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={"filepath": str(self.TRAIN_FILE)}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST, gen_kwargs={"filepath": str(self.TEST_FILE)}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"filepath": str(self.VAL_FILE)},
+            ),
+        ]
+
+    def _generate_examples(self, filepath: str):
+        df = pd.read_csv(filepath)
+        for idx, example in enumerate(df.itertuples(index=False)):
+            yield idx, {"text": example.text, "label": example.label}