wehub-resource-sync
75 lines
2.6 KiB
Python
75 lines
2.6 KiB
Python
import argparse
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import copy
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import json
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import os
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import sys
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from tqdm import tqdm
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sys.set_int_max_str_digits(0)
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sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
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from post_processors.code.clean import tag_cleaner
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("--input_file", type=str) # Use the dpo results file
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parser.add_argument("--output_file", type=str)
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parser.add_argument("--difficulty", type=str, default="introductory|interview")
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parser.add_argument("--prompt_file", type=str, )
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args = parser.parse_args()
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data = json.load(open(args.input_file))
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difficulty = args.difficulty.split("|")
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prompt_template = open(args.prompt_file).read()
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parent_dir = os.path.dirname(args.output_file)
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if not os.path.exists(parent_dir):
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os.makedirs(parent_dir)
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outputs = []
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for item in tqdm(data):
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if item["difficulty"] not in difficulty:
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continue
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for i, neg in enumerate(item["neg"]):
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question = item["question"]
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if item["starter_code"]:
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question = question + "\n\n" + item["starter_code"]
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neg_code = tag_cleaner(neg)
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if not neg_code:
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continue
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assert neg_code, (neg, item["question"])
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prompt = prompt_template.format(question=question, code=neg_code)
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new_item = copy.deepcopy(item)
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new_item["id"] = f"{item['problem_id']}_neg{i}"
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new_item["prompt"] = prompt
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new_item["neg_code"] = neg_code
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outputs.append(new_item)
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with open(args.output_file, "w") as f:
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for item in outputs:
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f.write(json.dumps(item) + "\n")
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if __name__ == "__main__":
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main()
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"""
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>>> python scripts/apps/pp_critique_difficulty.py \
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--input_file outputs/apps/apps.train.r2c.vanilla.gpt-4o.tem1.0.n11.exec.dpo_v1.0.json \
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--output_file outputs/apps/critique/apps.train.gpt4o.tem1.0.n11.neg.inputs.intro.inter.jsonl \
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--prompt_file prompts/apps/critique_0shot_v1.0.txt
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>>> python azure/gpt_crawler_mp.py \
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--prompt_file ../msranlpintern/reward_modeling/experiments/deepseek-coder-v1.5-ins.7b.apps.r2c.gpt4o.distil.A100.w8.v3.0.s42/apps/checkpoint-400/train.0shot.tem1.0.n10.v1.1.worsen_4o_critic.s42.f100k.jsonl \
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--outfile ../gpt-chat-examples/outputs/apps/critique/r2c.sft.train.0shot.tem1.0.n10.v1.1.worsen_4o_critic.s42.f100k.gpt4o.tem1.0.s42.n1.json_obj.jsonl \
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--model gpt-4o --max_gen_tokens 4096 --temperature 1.0 --num_processes 24 --seed 42 --n 1 --response_format json_object
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"""
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