tst

LongConL.py

@@ -30,8 +30,6 @@ _CONFIGS = {
     for task_name in TASK_NAMES
 }
 
-
-
 class LongConLDataset(datasets.GeneratorBasedBuilder):
     """Legal opinion classification dataset for LongConL tasks"""
 
@@ -73,39 +71,37 @@ class LongConLDataset(datasets.GeneratorBasedBuilder):
             ),
         ]
 
-	def _generate_examples(self, file_path):
-	    """Generate examples from the dataset CSV."""
-	    data = pd.read_csv(file_path)
-	    print("Data loaded from file:", file_path)
-	    print(data.head())  # Display first few rows
-
-	    # Check if the DataFrame is empty or has the correct columns
-	    if data.empty:
-		print(f"Warning: No data found in {file_path}")
-		return  # Early exit if there's no data
-	    
-	    expected_columns = {"Citation", "Full Case Name", "Opinion Text", "Numerical Label", "Text Label"}
-	    if not expected_columns.issubset(data.columns):
-		print(f"Warning: Missing columns in {file_path}. Expected columns: {expected_columns}. Found columns: {set(data.columns)}")
-		return  # Early exit if columns are missing
-
-	    data_dict = data.to_dict(orient="records")
-	    print(f"Number of examples to generate: {len(data_dict)}")
-
-	    for id_, row in enumerate(data_dict):
-		yield id_, {
-		    "Citation": row["Citation"],
-		    "Full Case Name": row["Full Case Name"],
-		    "Opinion Text": row["Opinion Text"],
-		    "Numerical Label": row.get("Numerical Label", None),
-		    "Text Label": row["Text Label"],
-		}
-
-
-    # Use a dynamic config
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name=task_name, version=datasets.Version("1.0.0"), description=task_name)
-        for task_name in ["ATS-Jurisdiction", "ATS-FavorableJudgment","JRC-AREA1","DC-category", "SC-issueArea","SSC-ca_disp", "Chevron-Agency","CoA-geniss"]  # Add your task names here
-    ]
-
+    def _generate_examples(self, file_path):
+        """Generate examples from the dataset CSV."""
+        data = pd.read_csv(file_path)
+        print("Data loaded from file:", file_path)
+        print(data.head())  # Display first few rows
+
+        # Check if the DataFrame is empty or has the correct columns
+        if data.empty:
+            print(f"Warning: No data found in {file_path}")
+            return  # Early exit if there's no data
+        
+        expected_columns = {"Citation", "Full Case Name", "Opinion Text", "Numerical Label", "Text Label"}
+        if not expected_columns.issubset(data.columns):
+            print(f"Warning: Missing columns in {file_path}. Expected columns: {expected_columns}. Found columns: {set(data.columns)}")
+            return  # Early exit if columns are missing
+
+        data_dict = data.to_dict(orient="records")
+        print(f"Number of examples to generate: {len(data_dict)}")
+
+        for id_, row in enumerate(data_dict):
+            yield id_, {
+                "Citation": row["Citation"],
+                "Full Case Name": row["Full Case Name"],
+                "Opinion Text": row["Opinion Text"],
+                "Numerical Label": row.get("Numerical Label", None),
+                "Text Label": row["Text Label"],
+            }
+
+# Use a dynamic config
+BUILDER_CONFIGS = [
+    datasets.BuilderConfig(name=task_name, version=datasets.Version("1.0.0"), description=task_name)
+    for task_name in ["ATS-Jurisdiction", "ATS-FavorableJudgment", "JRC-AREA1", "DC-category", "SC-issueArea", "SSC-ca_disp", "Chevron-Agency", "CoA-geniss"]  # Add your task names here
+]