from datasets import load_dataset import argparse import json _vanilla_prompt = """You are an expert Python programmer, and here is your task: {} Your code should pass these tests: {} Please put your code into [BEGIN][END] block. """ _vanilla_prompt_emp = """You are an expert Python programmer, and here is your task: {} Your code should pass these tests: {} **REMEMBER** to tag your solution program with the following format: [BEGIN] [END] and then return back it to me. """ _description_prompt = """You are an expert Python programmer, and here is your task: {} Your code should pass these tests: {} **DO NOT** show me any code. Please use **NATURAL LANGUAGE** to describe your thoughts and implementation in details. Take care if your algorithm can pass the test cases by simulation. **REMEMBER** to tag your description with the following format: [BEGIN] [END] and then return back it to me. """ PROMPTS = { "vanilla": _vanilla_prompt, "vanilla_emp": _vanilla_prompt_emp, "description": _description_prompt, } def main(): parser = argparse.ArgumentParser() parser.add_argument("--sanitized", default=False, action="store_true") parser.add_argument("--output_file", type=str, required=True) parser.add_argument("--prompt_type", type=str, default="vanilla") args = parser.parse_args() if args.sanitized: dataset = load_dataset("mbpp", "sanitized", split="test").to_list() else: dataset = load_dataset("mbpp", split="test").to_list() prompt_key = "prompt" if args.sanitized else "text" outputs = [] for item in dataset: task_id = item["task_id"] query = item[prompt_key] test_cases = "\n".join(item["test_list"]) prompt = PROMPTS[args.prompt_type].format(query, test_cases) outputs.append({ "prompt": prompt, "task_id": task_id, }) with open(args.output_file, "w") as f: for item in outputs: f.write(json.dumps(item) + "\n") if __name__ == "__main__": main()