mirror of
https://github.com/open-thought/reasoning-gym.git
synced 2026-04-19 12:58:07 +00:00
5d7fbac0ad
* math prompt improvements * ignore brackets in complex_arithmetic results * improve additional instruction in prompt of polynomial_equations * more strict tests for score_answer in polynomial_equations * simplify special reward handling * fix test_intermediate_integration * fix sokoban dataset * add common dataset score_answer consistency test
66 lines
2 KiB
Python
66 lines
2 KiB
Python
"""Spell backward task generator"""
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import re
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from dataclasses import dataclass
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from random import Random
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from typing import Any, Optional
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from ..data import read_data_file
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from ..factory import ProceduralDataset, register_dataset
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@dataclass
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class SpellBackwardConfig:
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"""Configuration for spelling words backward task generation"""
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min_word_len: int = 3 # Minimum word length
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seed: Optional[int] = None
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size: int = 500 # Virtual dataset size
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def validate(self) -> None:
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"""Validate configuration parameters"""
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assert self.min_word_len > 0, "min_word_len must be positive"
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class SpellBackwardDataset(ProceduralDataset):
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"""Generates tasks to spell words backward"""
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def __init__(self, config: SpellBackwardConfig):
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super().__init__(config=config, seed=config.seed, size=config.size)
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# Load and preprocess text
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text = read_data_file("in_the_year_2889.txt")
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# Extract words and clean them to contain only alphanumeric characters
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self.words = [
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word for word in re.findall(r"\b\w+\b", text) if word.isalnum() and len(word) >= config.min_word_len
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]
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def __getitem__(self, idx: int) -> dict:
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"""Generate a single spell backward task"""
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rng = Random(self.seed + idx)
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# Select random word
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word = rng.choice(self.words)
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answer = word[::-1]
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return {
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"question": f"Spell this word backward (example: sun -> nus): {word}",
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"answer": answer,
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"metadata": {"word": word, "word_len": len(word)},
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}
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def score_answer(self, answer: Optional[str], entry: dict[str, Any]) -> float:
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reward = 0.0
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expected_answer = entry["answer"]
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if isinstance(answer, str):
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try:
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if expected_answer.lower() == answer.lower():
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reward = 1.0
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else:
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reward = 0.05
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except:
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reward = 0.0
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return reward
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register_dataset("spell_backward", SpellBackwardDataset, SpellBackwardConfig)
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