mirror of
https://github.com/InternLM/InternBootcamp.git
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a8249acc18
* feat(run_eval): add checkpoint resume functionality and update example documentation; - update new bootcamp benchmark dataset * refactor(data_pipeline): optimize data generation pipeline; add multiple preset configurations for data generation * docs: update bootcamp list and add new scripts - Update Fulllist_InternBootcamp.md with new bootcamps and categories - Add new scripts to .gitignore: - examples/pipelines/filter_autogen_configs.py - examples/pipelines/quickgen_data_configs_from_eval_meta.py - Update dependencies in setup.py: - Add scipy and scikit-learn * refactor(internbootcamp): update bootcamp modules and improve error handling - Update import statements in __init__.py files - Add timestamp to target directory name in verl_data_preprocess.py - Improve error handling and scoring logic in bootcamp_judger.py - Remove unnecessary comments and update puzzle descriptions in multiple files
121 lines
No EOL
3.6 KiB
Python
121 lines
No EOL
3.6 KiB
Python
import re
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import json
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import numpy as np
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from internbootcamp.bootcamp.base import Basebootcamp
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def last_boxed_only_string(string):
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idx = string.rfind("\\boxed")
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if "\\boxed " in string:
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return "\\boxed " + string.split("\\boxed ")[-1].split("$")[0]
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if idx < 0:
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idx = string.rfind("\\fbox")
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if idx < 0:
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return None
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i = idx
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right_brace_idx = None
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num_left_braces_open = 0
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while i < len(string):
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if string[i] == "{":
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num_left_braces_open += 1
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if string[i] == "}":
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num_left_braces_open -= 1
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if num_left_braces_open == 0:
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right_brace_idx = i
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break
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i += 1
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if right_brace_idx is None:
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retval = None
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else:
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retval = string[idx:right_brace_idx + 1]
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return retval
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def remove_boxed(s):
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if "\\boxed " in s:
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left = "\\boxed "
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assert s[:len(left)] == left
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return s[len(left):]
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left = "\\boxed{"
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assert s[:len(left)] == left
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assert s[-1] == "}"
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return s[len(left):-1]
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class Earthtyphoonbootcamp(Basebootcamp):
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def __init__(
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self,
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v_range=(0, 100),
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seed=None
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):
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self.v_range = v_range
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if seed is not None:
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np.random.seed(seed)
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def case_generator(self):
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# 1. 随机采样参数 v
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v = float(np.random.uniform(*self.v_range))
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mslp = 1021.36 - 0.36*v - (v/20.16)**2
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return {"v": v, "mslp": mslp}
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def prompt_func(self, identity) -> str:
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v = identity["v"]
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return (
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f"下面给出最大风速（v）={v} (kt)\n\n"
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"请计算平均海平面气压（单位是 百帕 hPa），计算公式为：\n"
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"mslp = 1021.36 - 0.36*v - (v/20.16)**2\n"
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"请将最终计算结果放入\\boxed{}中，例如：\\boxed{1234.56}"
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)
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@staticmethod
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def extract_output(output: str) -> str:
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# 用正则提取“mslp = …”右侧的表达式
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output = last_boxed_only_string(output)
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if output is None:
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return ""
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return remove_boxed(output)
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@classmethod
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def _verify_correction(cls, solution: str, identity: dict) -> bool:
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# 解析 LLM 给出的系数 c，形如 “c*x”
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solution = solution.replace(" ", "")
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try:
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c = float(solution)
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except:
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return False
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# print(c)
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# 验证 c ≈ k
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if abs(c - identity["mslp"]) < 1e-2:
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return 1
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return 0
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if __name__ == "__main__":
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bootcamp = Earthtyphoonbootcamp(seed=123)
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# 生成几个样例
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examples = [bootcamp.case_generator() for _ in range(3)]
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print(examples)
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print(bootcamp.prompt_func(examples[0]))
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solution = bootcamp.extract_output("xxxxx relative mslp = \\boxed{984.35},that is true ")
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print(solution ,bootcamp._verify_correction(solution, examples[0]))
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solution = bootcamp.extract_output("xxxxx relative mslp = \\boxed{985.35}, haha ")
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print(solution, bootcamp._verify_correction(solution, examples[0]))
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# for identity in examples:
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# # 构造“模型”返回答案，模拟 LLM 的输出
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# humidity = identity["v"]
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# sol = f"{humidity:.4f}"
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# # 调用 Basebootcamp 提供的 verify_score 接口进行验证
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# score = bootcamp.verify_score(sol, identity, short_threshold=1e-2)
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# # 打印结果
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# print(json.dumps({
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# "identity": identity,
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# "solution": sol,
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# "verify_score": score
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# }, ensure_ascii=False, indent=2)) |