reasoning-gym/reasoning_gym/games/sudoku.py
Andreas Köpf b59ccdefa2
Merge pull request #178 from olliestanley/feature/unsloth-train
Add minimal working GRPO training example with Unsloth
2025-02-21 15:37:24 +01:00

254 lines
8.9 KiB
Python

"""Sudoku puzzle generator"""
import copy
from dataclasses import dataclass
from random import Random
from typing import Any, Optional
from ..factory import ProceduralDataset, register_dataset
@dataclass
class SudokuConfig:
"""
Configuration for sudoku puzzle generation
Puzzle generation can be a bit slower for puzzles with a high (~60+) number of empty cells
"""
min_empty: int = 30 # Minimum number of empty cells
max_empty: int = 50 # Maximum number of empty cells
seed: Optional[int] = None
size: int = 500 # Virtual dataset size
def validate(self):
"""Validate configuration parameters"""
# 81 - 64 = 17, the minimum number of clues required for 9x9 Sudoku to have a unique solution
assert 0 <= self.min_empty <= 64, "min_empty must be between 0 and 64"
assert self.min_empty <= self.max_empty <= 64, "max_empty must be between min_empty and 64"
class SudokuDataset(ProceduralDataset):
"""Generates sudoku puzzles with configurable difficulty"""
def __init__(self, config: SudokuConfig):
super().__init__(config=config, seed=config.seed, size=config.size)
def __len__(self) -> int:
return self.config.size
def __iter__(self):
self._current_idx = 0
return self
def __next__(self):
if self._current_idx >= self.config.size:
raise StopIteration
item = self[self._current_idx]
self._current_idx += 1
return item
def _is_valid(self, board: list[list[int]], row: int, col: int, num: int) -> bool:
"""Check if number can be placed at position"""
# Check row
if num in board[row]:
return False
# Check column
if num in [board[i][col] for i in range(9)]:
return False
# Check 3x3 box
box_row, box_col = 3 * (row // 3), 3 * (col // 3)
for i in range(box_row, box_row + 3):
for j in range(box_col, box_col + 3):
if board[i][j] == num:
return False
return True
def _get_possible_values(self, board: list[list[int]], row: int, col: int) -> set[int]:
"""Get all possible values for a cell."""
row_values = set(board[row])
col_values = set(board[i][col] for i in range(9))
# Get filled values in the current 3x3 subgrid
box_row, box_col = 3 * (row // 3), 3 * (col // 3)
box_values = set()
for i in range(box_row, box_row + 3):
for j in range(box_col, box_col + 3):
box_values.add(board[i][j])
used_values = row_values | col_values | box_values
return set(range(1, 10)) - used_values
def _solve(self, board: list[list[int]]) -> bool:
"""Solve sudoku using backtracking"""
empty = self._find_empty(board)
if not empty:
return True
row, col = empty
for num in self._get_possible_values(board, row, col):
board[row][col] = num
if self._solve(board):
return True
board[row][col] = 0
return False
def _find_empty(self, board: list[list[int]]) -> Optional[tuple[int, int]]:
"""Find an empty cell"""
for i in range(9):
for j in range(9):
if board[i][j] == 0:
return (i, j)
return None
def _generate_solved_board(self, rng: Random) -> list[list[int]]:
"""Generate a complete solved sudoku board"""
board = [[0] * 9 for _ in range(9)]
# Fill diagonal boxes first (they are independent)
for i in range(0, 9, 3):
nums = list(range(1, 10))
rng.shuffle(nums)
pos = 0
for r in range(i, i + 3):
for c in range(i, i + 3):
board[r][c] = nums[pos]
pos += 1
# Solve the rest
self._solve(board)
return board
def _count_solutions(self, board: list[list[int]], limit: int = 2) -> int:
"""Count the number of solutions for a given board"""
def _get_min_possibilities_cell(board: list[list[int]]) -> Optional[tuple[int, int, set[int]]]:
"""
Get the cell with the lowest number of possibilities.
Returns None if the board is already solved.
"""
min_possibilities = 10
min_cell = None
min_values = None
for i in range(9):
for j in range(9):
if board[i][j] == 0:
possible = self._get_possible_values(board, i, j)
if len(possible) < min_possibilities:
min_possibilities = len(possible)
min_cell = (i, j)
min_values = possible
if min_possibilities == 1:
return (*min_cell, min_values)
return (*min_cell, min_values) if min_cell else None
def _count_solutions_helper(board: list[list[int]]) -> int:
cell_info = _get_min_possibilities_cell(board)
if not cell_info:
return 1
row, col, possible_values = cell_info
count = 0
for num in possible_values:
board[row][col] = num
count += _count_solutions_helper(board)
if count >= limit:
return count
board[row][col] = 0
return count
return _count_solutions_helper(board)
def _create_puzzle(self, solved_board: list[list[int]], num_empty: int, rng: Random) -> list[list[int]]:
"""Create puzzle by removing numbers from solved board"""
puzzle = [row[:] for row in solved_board]
cells = [(i, j) for i in range(9) for j in range(9)]
rng.shuffle(cells)
num_removed = 0
for i, j in cells:
saved = puzzle[i][j]
puzzle[i][j] = 0
puzzle_copy = copy.deepcopy(puzzle)
# Check if removing this clue breaks uniqueness
if self._count_solutions(puzzle_copy) > 1:
puzzle[i][j] = saved
else:
num_removed += 1
if num_removed == num_empty:
break
return puzzle
def _board_to_string(self, board: list[list[int]]) -> str:
"""Convert board to string representation"""
return "\n".join(" ".join(str(x) if x != 0 else "_" for x in row) for row in board)
def __getitem__(self, idx: int) -> dict:
"""Generate a single sudoku puzzle"""
rng = Random(self.seed + idx)
# Generate solved board
solved_board = self._generate_solved_board(rng)
# Create puzzle by removing numbers
num_empty = rng.randint(self.config.min_empty, self.config.max_empty)
puzzle = self._create_puzzle(solved_board, num_empty, rng)
# Format as strings
puzzle_str = self._board_to_string(puzzle)
solution_str = self._board_to_string(solved_board)
question = (
f"Solve this Sudoku puzzle:\n{puzzle_str}\n"
"Respond with only your answer, formatted as the puzzle, a 9x9 grid with numbers separated by spaces, and rows separated by newlines."
)
return {
"question": question,
"answer": solution_str,
"metadata": {"puzzle": puzzle, "solution": solved_board, "num_empty": num_empty},
}
def score_answer(self, answer: Optional[str], entry: dict[str, Any]) -> float:
if not answer:
return 0.0
oracle_answer = entry["answer"]
metadata = entry["metadata"]
solution: list[list[int]] = metadata["solution"]
board_size: int = len(solution[0])
# 1. match answer without trailing whitespaces
answer_stripped = "\n".join(l.rstrip() for l in answer.split("\n"))
oracle_answer_stripped = "\n".join(l.rstrip() for l in oracle_answer.split("\n"))
if answer_stripped == oracle_answer_stripped:
reward = 1.0
else:
# 2. accept answers with correct numeric sequence (ignoring non-numeric characters)
row = 0
num_matching = 0
for ln in answer.split("\n"):
if row >= len(solution):
break
numbers = [int(c) for c in ln if c in "123456789"]
if len(numbers) != board_size:
continue # ignore lines without numbers
for a, b in zip(solution[row], numbers):
if a == b:
num_matching += 1
row += 1
reward = num_matching / (board_size * board_size)
reward *= 0.9 # penalty for not using standard format
if len(answer) > len(oracle_answer):
reward *= len(oracle_answer) / len(answer) # penalty for additional length
return reward
register_dataset("sudoku", SudokuDataset, SudokuConfig)