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https://github.com/open-thought/reasoning-gym.git
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* feat: Add optional curriculum support to dataset registration and creation * docs: Add docstrings to create_curriculum() and register_dataset() * feat: Add curriculum configuration classes for CurriculumExperiment * feat: Add weight parameter to CurriculumAttributeConfig and use in DatasetSpec * refactor: Simplify CurriculumAttributeConfig with "*" attribute level support * test: Add unit tests for CurriculumExperiment class * feat: Add from_yaml() method to CurriculumExperimentConfig with unit test
195 lines
7.4 KiB
Python
195 lines
7.4 KiB
Python
"""Find the largest island in a grid of 1s and 0s.
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A popular Leetcode problem:
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https://leetcode.com/problems/max-area-of-island/description/
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"""
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from collections import deque
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from dataclasses import dataclass
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from random import Random
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from typing import Optional
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from ..coaching import AttributeType, BaseCurriculum, RangeAttributeDefinition
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from ..factory import ProceduralDataset, register_dataset
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QUESTION_TEMPLATE = """You are given the following {rows} x {cols} binary matrix grid:
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{grid}
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An island is a group of 1's (representing land) connected 4-directionally (horizontal or vertical).
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You may assume all four edges of the grid are surrounded by water.
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The area of an island is the number of cells with a value 1 in the island.
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Return the maximum area of an island in grid. If there is no island, return 0.
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"""
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@dataclass
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class LargestIslandConfig:
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"""Configuration for Largest Island dataset generation"""
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min_rows: int = 5 # Minimum number of rows in the grid
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max_rows: int = 10 # Maximum number of rows in the grid
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min_cols: int = 5 # Minimum number of columns in the grid
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max_cols: int = 10 # Maximum number of columns in the grid
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min_num_islands: int = 0
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max_num_islands: int = (
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5 # Maximum number of islands (actual max might be smaller due to merging of islands during random walk)
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)
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min_island_size: int = 0
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max_island_size: int = (
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10 # Maximum size of an island (actual max might be larger due to merging of islands during random walk)
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)
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size: int = 500 # Virtual dataset size
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seed: Optional[int] = None
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def validate(self):
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"""Validate configuration parameters"""
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assert 1 <= self.min_rows <= self.max_rows, "Invalid rows range"
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assert 1 <= self.min_cols <= self.max_cols, "Invalid cols range"
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assert 0 <= self.min_num_islands <= self.max_num_islands, "Invalid num_islands range"
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assert 0 <= self.min_island_size <= self.max_island_size, "Invalid island_size range"
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class LargestIslandDataset(ProceduralDataset):
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"""Generates Largest Island exercises with configurable difficulty"""
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def __init__(self, config: LargestIslandConfig):
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super().__init__(config=config, seed=config.seed, size=config.size)
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def _is_valid_cell(self, r: int, c: int, rows: int, cols: int) -> bool:
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return 0 <= r < rows and 0 <= c < cols
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def _create_grid(self, rng: Random, rows: int, cols: int) -> list[list[int]]:
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"""Create a random grid of islands using a random walk algorithm"""
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grid = [[0] * cols for _ in range(rows)]
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directions = [(-1, 0), (1, 0), (0, -1), (0, 1)] # Up, Down, Left, Right
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def create_island():
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r, c = rng.randint(0, rows - 1), rng.randint(0, cols - 1)
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capped_size = min(rng.randint(self.config.min_island_size, self.config.max_island_size), rows * cols)
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for _ in range(capped_size):
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grid[r][c] = 1
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rng.shuffle(directions)
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for dr, dc in directions:
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new_r, new_c = r + dr, c + dc
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if self._is_valid_cell(new_r, new_c, rows, cols) and grid[new_r][new_c] == 0:
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r, c = new_r, new_c
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break
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num_islands = rng.randint(self.config.min_num_islands, self.config.max_num_islands)
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for _ in range(num_islands):
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create_island()
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return grid
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def _get_largest_island(self, grid: list[list[int]]) -> int:
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"""Find the largest island in the grid"""
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rows, cols = len(grid), len(grid[0])
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directions = [(-1, 0), (1, 0), (0, -1), (0, 1)] # Up, Down, Left, Right
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visited = set()
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def bfs(r, c):
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area = 1
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visited.add((r, c))
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queue = deque([(r, c)])
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while queue:
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r, c = queue.popleft()
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for dr, dc in directions:
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new_r, new_c = r + dr, c + dc
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if (
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self._is_valid_cell(new_r, new_c, rows, cols)
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and (new_r, new_c) not in visited
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and grid[new_r][new_c] == 1
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):
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area += 1
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visited.add((new_r, new_c))
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queue.append((new_r, new_c))
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return area
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max_area = 0
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for r in range(rows):
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for c in range(cols):
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if grid[r][c] == 1 and (r, c) not in visited:
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max_area = max(max_area, bfs(r, c))
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return max_area
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def _grid_to_string(self, grid: list[list[int]]) -> str:
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"""Convert grid to a string representation"""
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return "\n".join(" ".join(str(cell) for cell in row) for row in grid)
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def _string_to_board(self, grid_str: str) -> list[list[int]]:
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"""Convert string representation to a grid"""
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return [[int(cell) for cell in row.split()] for row in grid_str.split("\n")]
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def __getitem__(self, idx: int) -> dict:
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"""Generate a single Largest Island question"""
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rng = Random(self.seed + idx)
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rows = rng.randint(self.config.min_rows, self.config.max_rows)
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cols = rng.randint(self.config.min_cols, self.config.max_cols)
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grid = self._create_grid(rng, rows, cols)
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grid_str = self._grid_to_string(grid)
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answer = self._get_largest_island(grid)
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return {
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"question": QUESTION_TEMPLATE.format(rows=rows, cols=cols, grid=grid_str),
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"answer": str(answer),
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"metadata": {"grid": grid, "solution": answer},
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}
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class LargestIslandCurriculum(BaseCurriculum):
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def __init__(self):
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super().__init__(LargestIslandCurriculum.__name__, LargestIslandConfig)
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# Define attributes
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self._define_attributes(
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RangeAttributeDefinition(
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name="rows",
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levels=[5, 10, 50, 100],
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default_level=0,
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description="Number of rows in the grid",
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attr_type=AttributeType.APPEND,
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min_value=1,
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lower_field_name="min_rows",
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upper_field_name="max_rows",
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),
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RangeAttributeDefinition(
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name="cols",
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levels=[5, 10, 50, 100],
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default_level=0,
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description="Number of columns in the grid",
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attr_type=AttributeType.APPEND,
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min_value=1,
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lower_field_name="min_cols",
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upper_field_name="max_cols",
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),
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RangeAttributeDefinition(
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name="num_islands",
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levels=[2, 5, 10, 20],
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default_level=0,
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description="Number of islands in the grid",
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attr_type=AttributeType.APPEND,
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min_value=0,
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lower_field_name="min_num_islands",
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upper_field_name="max_num_islands",
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),
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RangeAttributeDefinition(
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name="island_size",
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levels=[5, 10, 20, 30],
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default_level=0,
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description="Size of the islands in the grid",
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attr_type=AttributeType.APPEND,
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min_value=0,
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lower_field_name="min_island_size",
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upper_field_name="max_island_size",
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),
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)
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register_dataset("largest_island", LargestIslandDataset, LargestIslandConfig, LargestIslandCurriculum)
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