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import argparse |
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import json |
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from pathlib import Path |
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import pandas as pd |
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from tqdm import tqdm |
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from project_settings import project_path |
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def get_args(): |
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parser = argparse.ArgumentParser() |
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parser.add_argument( |
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"--data_dir", |
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default=(project_path / "original_data/weibo-400w").as_posix(), |
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type=str |
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) |
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parser.add_argument( |
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"--output_file", |
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default=(project_path / "data/weibo.jsonl"), |
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type=str |
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) |
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args = parser.parse_args() |
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return args |
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def main(): |
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args = get_args() |
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data_dir = Path(args.data_dir) |
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questions = list() |
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with open(data_dir / "stc_weibo_train_post", "r", encoding="utf-8") as f: |
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for row in f: |
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row = str(row).strip() |
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row = "".join(row.split()) |
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questions.append(row) |
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answers = list() |
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with open(data_dir / "stc_weibo_train_response.part", "r", encoding="utf-8") as f: |
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for row in f: |
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row = str(row).strip() |
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row = "".join(row.split()) |
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answers.append(row) |
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if len(questions) != len(answers): |
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raise AssertionError |
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with open(args.output_file, "w", encoding="utf-8") as f: |
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for question, answer in tqdm(zip(questions, answers)): |
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row = { |
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"conversation": [ |
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{"role": "human", "message": question}, |
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{"role": "assistant", "message": answer}, |
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], |
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"category": None, |
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"data_source": "weibo", |
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} |
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row = json.dumps(row, ensure_ascii=False) |
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f.write("{}\n".format(row)) |
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return |
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if __name__ == '__main__': |
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main() |
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