| from datasets import DatasetDict, load_dataset | |
| import csv | |
| import json | |
| def main(): | |
| label2id = {"positive": 2, "neutral": 1, "negative": 0} | |
| for split in ["train", "test"]: | |
| input_file = csv.DictReader(open(f"raw_data/{split}_csv")) | |
| with open(f'{split}.jsonl', 'w') as fOut: | |
| for row in input_file: | |
| fOut.write(json.dumps({'id': row['textID'], 'text': row['text'], 'label': label2id[row['sentiment']], 'label_text': row['sentiment']})+"\n") | |
| """ | |
| train_dset = load_dataset("csv", data_files="raw_data/train_csv", split="train") | |
| train_dset = train_dset.remove_columns(["selected_text"]) | |
| test_dset = load_dataset("csv", data_files="raw_data/train_csv", split="train") | |
| raw_dset = DatasetDict() | |
| raw_dset["train"] = train_dset | |
| raw_dset["test"] = test_dset | |
| for split, dset in raw_dset.items(): | |
| dset = dset.rename_column("sentiment", "label_text") | |
| dset = dset.map(lambda x: {"label": label2id[x["label_text"]]}, num_proc=8) | |
| dset.to_json(f"{split}.jsonl") | |
| """ | |
| if __name__ == "__main__": | |
| main() |