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include ranges rather than sampled values in difficulty metadata dicts (#387)

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* update difficulty metadata for logic datasets

* update difficulty metadata for graph datasets

* update difficulty metadata for geometry datasets

* update difficulty metadata for games datasets

* update difficulty metadata for cognition datasets

* update difficulty metadata for arithmetic datasets

* update difficulty metadata for arc datasets

* update difficulty metadata for algorithmic datasets

* update difficulty metadata for algebra datasets

* use tuples

* update tests

* update tests
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Oliver Stanley 2025-03-20 09:27:03 +00:00 • committed by GitHub
parent b69c35818a
commit 7475a20700
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80 changed files with 304 additions and 126 deletions
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reasoning_gym/games/sokoban.py
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@ -65,7 +65,7 @@ class SokobanDataset(ProceduralDataset):
# Make the Sokoban!
rng = Random(self.seed + idx)
gamestr, solution, difficulty = self._generate(
gamestr, solution, puzzle_data = self._generate(
rng=rng,
min_w=self.config.min_w,
min_h=self.config.min_h,
@ -93,7 +93,15 @@ Here is your puzzle:
"""
+ gamestr,
"answer": solution,
"metadata": {"gamestr": gamestr, "difficulty": difficulty},
"metadata": {
"gamestr": gamestr,
"width": puzzle_data["width"],
"height": puzzle_data["height"],
"difficulty": {
"width": (self.config.min_w, self.config.max_w),
"height": (self.config.min_h, self.config.max_h),
},
},
}
def score_answer(self, answer: Optional[str], entry: dict[str, Any]) -> float: