Create conve.py

conve.py

@@ -0,0 +1,48 @@
+import pandas as pd
+from rich import print
+from datasets import DatasetDict, Value, ClassLabel, Dataset,  Features
+
+
+def load_dataset(input_url, label_url):
+    input_df = pd.read_csv(input_url)
+    label_df = pd.read_csv(label_url, header=None)
+
+    input_df.columns = ['id', 'context', 'answerA', 'answerB', 'answerC']
+    label_df.columns = ['id', 'label']
+
+    features = Features({
+        'context':  Value('string'), 
+        'answerA':  Value('string'), 
+        'answerB':  Value('string'), 
+        'answerC':  Value('string'), 
+        'label':  ClassLabel(num_classes=3, names=['A', 'B', 'C']), 
+    })
+    dataset = Dataset.from_dict({
+        'context': input_df['context'], 
+        'answerA': input_df['answerA'], 
+        'answerB': input_df['answerB'], 
+        'answerC': input_df['answerC'], 
+        'label': label_df['label']
+    }, features=features)
+    return dataset
+
+
+input_url = 'https://raw.githubusercontent.com/wangcunxiang/SemEval2020-Task4-Commonsense-Validation-and-Explanation/master/ALL%20data/Training%20%20Data/subtaskB_data_all.csv'
+label_url = 'https://raw.githubusercontent.com/wangcunxiang/SemEval2020-Task4-Commonsense-Validation-and-Explanation/master/ALL%20data/Training%20%20Data/subtaskB_answers_all.csv'
+train_dataset = load_dataset(input_url, label_url)
+
+input_url = 'https://raw.githubusercontent.com/wangcunxiang/SemEval2020-Task4-Commonsense-Validation-and-Explanation/master/ALL%20data/Dev%20Data/subtaskB_dev_data.csv'
+label_url = 'https://raw.githubusercontent.com/wangcunxiang/SemEval2020-Task4-Commonsense-Validation-and-Explanation/master/ALL%20data/Dev%20Data/subtaskB_gold_answers.csv'
+validation_dataset = load_dataset(input_url, label_url)
+
+input_url = 'https://raw.githubusercontent.com/wangcunxiang/SemEval2020-Task4-Commonsense-Validation-and-Explanation/master/ALL%20data/Test%20Data/subtaskB_test_data.csv'
+label_url = 'https://raw.githubusercontent.com/wangcunxiang/SemEval2020-Task4-Commonsense-Validation-and-Explanation/master/ALL%20data/Test%20Data/subtaskB_gold_answers.csv'
+test_dataset = load_dataset(input_url, label_url)
+
+dataset = DatasetDict({
+    'train': train_dataset, 
+    'validation': validation_dataset, 
+    'test': test_dataset
+})
+print(dataset)
+dataset.push_to_hub('extraordinarylab/comve_taskb')