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