mirror of
https://github.com/princeton-nlp/tree-of-thought-llm
synced 2024-11-28 15:04:07 +00:00
69 lines
2.8 KiB
Python
69 lines
2.8 KiB
Python
import os
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import json
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import argparse
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from tot.tasks import get_task
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from tot.methods.bfs import solve, naive_solve
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from tot.models import gpt_usage
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def run(args):
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task = get_task(args.task)
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logs, cnt_avg, cnt_any = [], 0, 0
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if args.naive_run:
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file = f'./logs/{args.task}/{args.backend}_{args.temperature}_naive_{args.prompt_sample}_sample_{args.n_generate_sample}_start{args.task_start_index}_end{args.task_end_index}.json'
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else:
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file = f'./logs/{args.task}/{args.backend}_{args.temperature}_{args.method_generate}{args.n_generate_sample}_{args.method_evaluate}{args.n_evaluate_sample}_{args.method_select}{args.n_select_sample}_start{args.task_start_index}_end{args.task_end_index}.json'
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os.makedirs(os.path.dirname(file), exist_ok=True)
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for i in range(args.task_start_index, args.task_end_index):
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# solve
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if args.naive_run:
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ys, info = naive_solve(args, task, i)
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else:
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ys, info = solve(args, task, i)
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# log
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infos = [task.test_output(i, y) for y in ys]
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info.update({'idx': i, 'ys': ys, 'infos': infos, 'usage_so_far': gpt_usage(args.backend)})
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logs.append(info)
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with open(file, 'w') as f:
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json.dump(logs, f, indent=4)
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# log main metric
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accs = [info['r'] for info in infos]
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cnt_avg += sum(accs) / len(accs)
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cnt_any += any(accs)
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print(i, 'sum(accs)', sum(accs), 'cnt_avg', cnt_avg, 'cnt_any', cnt_any, '\n')
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n = args.task_end_index - args.task_start_index
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print(cnt_avg / n, cnt_any / n)
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print('usage_so_far', gpt_usage(args.backend))
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def parse_args():
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args = argparse.ArgumentParser()
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args.add_argument('--backend', type=str, choices=['gpt-4', 'gpt-3.5-turbo'], default='gpt-4')
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args.add_argument('--temperature', type=float, default=0.7)
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args.add_argument('--task', type=str, required=True, choices=['game24', 'text', 'crosswords'])
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args.add_argument('--task_start_index', type=int, default=900)
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args.add_argument('--task_end_index', type=int, default=1000)
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args.add_argument('--naive_run', action='store_true')
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args.add_argument('--prompt_sample', type=str, choices=['standard', 'cot']) # only used when method_generate = sample, or naive_run
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args.add_argument('--method_generate', type=str, choices=['sample', 'propose'])
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args.add_argument('--method_evaluate', type=str, choices=['value', 'vote'])
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args.add_argument('--method_select', type=str, choices=['sample', 'greedy'], default='greedy')
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args.add_argument('--n_generate_sample', type=int, default=1) # only thing needed if naive_run
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args.add_argument('--n_evaluate_sample', type=int, default=1)
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args.add_argument('--n_select_sample', type=int, default=1)
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args = args.parse_args()
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return args
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if __name__ == '__main__':
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args = parse_args()
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print(args)
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run(args) |