scripts

LongConL.py

@@ -1,99 +1,90 @@
+# LongConL dataset script
 import datasets
-from datasets import DatasetInfo, Features, Value, Sequence, SplitGenerator
 import pandas as pd
-from pathlib import Path
 
-# Constants for the dataset
-_CITATION = """"""
-_DESCRIPTION = """Legal opinion classification dataset containing multiple tasks."""
-_HOMEPAGE = "https://huggingface.co/datasets/reglab/LongConL"
-
-# Define your configurations for each task dynamically
-TASKS = ["ATS-Jurisdiction"]  # Add all task names here
 
-# Configs for each task
-_CONFIGS = {
-    task: {
-        "description": f"Task: {task}",
-        "features": Features({
-            "Citation": Value("string"),
-            "Case Name": Value("string"),
-            "Opinion Text": Value("string"),
-            "Numerical Label": Value("string"),  # Assuming labels are strings, adjust if different
-            "Text Label": Value("string"),
-        }),
-        "license": None,
+_CITATION = """"""
+_DESCRIPTION = """"""
+_HOMEPAGE = ""
+_LICENSE = ""
+_URLS = {
+    "LongConL": {
+        "train": "data/LongConL-tasks/{task_name}/train.csv",
+        "validation": "data/LongConL-tasks/{task_name}/validation.csv",
+        "test": "data/LongConL-tasks/{task_name}/test.csv",
     }
-    for task in TASKS
 }
 
+_CONFIGS = {}
 
-class LongConLDataset(datasets.GeneratorBasedBuilder):
-    """Legal classification tasks for LongConL"""
+# Adding a config for each task in your dataset
+_CONFIGS["LongConL"] = {
+    "description": "Legal dataset containing various classification tasks.",
+    "features": {
+        "Citation": datasets.Value("string"),
+        "Case Name": datasets.Value("string"),
+        "Opinion Text": datasets.Value("string"),
+        "Numerical Label": datasets.Value("string"),  # Change to int32 if necessary
+        "Text Label": datasets.Value("string"),
+    },
+    "license": None,
+}
 
-    # Define configurations for each task in the dataset
+
+class LongConL(datasets.GeneratorBasedBuilder):
+    """LongConL legal annotation dataset for multiple tasks."""
+    
     BUILDER_CONFIGS = [
         datasets.BuilderConfig(
-            name=task, version=datasets.Version("1.0.0"), description=f"Task: {task}",
+            name=task, version=datasets.Version("1.0.0"), description=task,
         )
         for task in _CONFIGS
     ]
-
+    
     def _info(self):
-        """Return dataset information with task-specific features."""
+        """Returns the dataset's metadata."""
+        features = _CONFIGS[self.config.name]["features"]
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
-            features=_CONFIGS[self.config.name]["features"],
+            features=datasets.Features(features),
             homepage=_HOMEPAGE,
             citation=_CITATION,
             license=_CONFIGS[self.config.name]["license"],
         )
 
     def _split_generators(self, dl_manager):
-        """Return SplitGenerators based on the task name."""
-        task_name = self.config.name
-        base_dir = Path(f"data/LongConL-tasks/{task_name}")  # Path to task-specific directory
-
-        return [
-            SplitGenerator(
+        """Returns SplitGenerators for train, validation, and test sets."""
+        downloaded_file_dir = dl_manager.download_and_extract(_URLS["LongConL"])
+        
+        splits = [
+            datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
-                gen_kwargs={"file_path": base_dir / "train.csv"},
+                gen_kwargs={
+                    "fpath": downloaded_file_dir["train"],
+                    "name": self.config.name,
+                },
             ),
-            SplitGenerator(
+            datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION,
-                gen_kwargs={"file_path": base_dir / "validation.csv"},
+                gen_kwargs={
+                    "fpath": downloaded_file_dir["validation"],
+                    "name": self.config.name,
+                },
             ),
-            SplitGenerator(
+            datasets.SplitGenerator(
                 name=datasets.Split.TEST,
-                gen_kwargs={"file_path": base_dir / "test.csv"},
+                gen_kwargs={
+                    "fpath": downloaded_file_dir["test"],
+                    "name": self.config.name,
+                },
             ),
         ]
+        return splits
 
-    def _generate_examples(self, file_path):
-        """Yields examples from the CSV files."""
-        data = pd.read_csv(file_path)
-
-        # Iterate through each row and yield as example
-        for idx, row in data.iterrows():
-            yield idx, {
-                "Citation": row["Citation"],
-                "Case Name": row["Case Name"],
-                "Opinion Text": row["Opinion Text"],
-                "Numerical Label": row.get("Numerical Label", None),  # Optional column for tasks that may not have it
-                "Text Label": row["Text Label"],
-            }
-
-
-# Example usage
-if __name__ == "__main__":
-    # Load a specific task dataset by task name
-    dataset = datasets.load_dataset("reglab/LongConL", name="ATS-Jurisdiction")
-    
-    # Access train, validation, and test splits
-    train_dataset = dataset["train"]
-    validation_dataset = dataset["validation"]
-    test_dataset = dataset["test"]
-
-    # Print some examples
-    print(train_dataset)
+    def _generate_examples(self, fpath, name):
+        """Yields examples from each split as (key, example) tuples."""
+        data = pd.read_csv(fpath)
+        data = data.to_dict(orient="records")
+        for id_line, example in enumerate(data):
+            yield id_line, example
 

__init__.py

@@ -1,2 +1,2 @@
-from .LongConL import LongConLDataset
+
 

load-data.py

@@ -1,26 +1,4 @@
 from datasets import load_dataset
-from huggingface_hub import login
 
-# Login to Hugging Face using your token
-login(token="")
-
-# Specify the task name you want to load
-task_name = "ATS-Jurisdiction"  # Replace with the task you want
-
-try:
-    # Load the dataset with the dynamic task name
-    dataset = load_dataset("reglab/LongConL", name=task_name)  # Using dynamic task name
-
-    # Access train, validation, and test splits
-    train_dataset = dataset['train']
-    validation_dataset = dataset['validation']
-    test_dataset = dataset['test']
-
-    # Use the datasets as needed
-    print("Train Dataset:", train_dataset)
-    print("Validation Dataset:", validation_dataset)
-    print("Test Dataset:", test_dataset)
-
-except Exception as e:
-    print(f"An error occurred: {e}")
+dataset = load_dataset("reglab/LongConL", use_auth_token=your_token)