wehub-resource-sync
117 lines
2.9 KiB
Python
117 lines
2.9 KiB
Python
import copy
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import json
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import re
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import sys
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from argparse import ArgumentParser
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import json
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from datasets import load_dataset
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from tqdm import tqdm
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sys.set_int_max_str_digits(0)
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_vanilla_prompt = """You are an expert programmer. Here is a programming problem:
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{}
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------------------------
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And here is one group of test case inputs:
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```
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{}
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```
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------------------------
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Please carefully comprehend the process described in the problem, and simulate it **step-by-step** to obtain the expected outputs the above test case inputs.
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**REMEMBER** to follow the format below to provide the outputs:
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[BEGIN]
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outputs
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[END]
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"""
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_vanilla_prompt_2 = """You are an expert programmer. Here is a programming problem:
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{}
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------------------------
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And here is one group of test case inputs:
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```
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{}
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```
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------------------------
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Please carefully comprehend the process described in the problem, and derive the expected outputs the above test case inputs. You should follow the steps below:
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(1) Simulate the algorithm/process described in the problem with the given inputs **step-by-step**, and record the step-level intermediate results.
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(2) Derive the correct outcome.
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(3) Put the final outputs in the format below:
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[BEGIN]
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*put your outputs here*
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[END]
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and return back it to me.
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"""
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_vanilla_prompt_3 = """You are an expert programmer. Here is a programming problem:
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{}
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------------------------
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And here is one group of test case inputs:
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```
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{}
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```
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------------------------
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Please carefully comprehend the process described in the problem, and derive the expected outputs the above test case inputs. You should follow the steps below:
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(1) Simulate the algorithm/process described in the problem with the given inputs **step-by-step**, and record the step-level intermediate results.
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(2) Derive the correct outcome.
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Response format:
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[BEGIN]
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*The expected outputs*
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[END]
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"""
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PROMPTS = {
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"vanilla": _vanilla_prompt,
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"vanilla_2": _vanilla_prompt_2,
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"vanilla_3": _vanilla_prompt_3,
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}
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def main():
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parser = ArgumentParser()
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parser.add_argument("--split", type=str, required=True)
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parser.add_argument("--output_file", type=str, required=True)
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parser.add_argument("--prompt_type", type=str, default="vanilla")
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args = parser.parse_args()
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data = load_dataset("codeparrot/apps", split=args.split).to_list()
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print(len(data))
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inputs = []
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for item in data:
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if item["input_output"]:
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item["input_output"] = json.loads(item["input_output"])
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inputs.append(item)
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with open(args.output_file, "w") as f:
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for item in tqdm(inputs, total=len(inputs)):
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problem = item["question"]
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for case in item["input_output"]["inputs"]:
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new_item = copy.deepcopy(item)
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prompt = PROMPTS[args.prompt_type].format(problem, case)
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new_item["prompt"] = prompt
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f.write(json.dumps(new_item) + "\n")
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if __name__ == '__main__':
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main()
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"""
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"""
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