| 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') |