|
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({'textID': 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() |
|
|