mirror of
https://github.com/open-thought/reasoning-gym.git
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7475a20700
* 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
181 lines
7.3 KiB
Python
181 lines
7.3 KiB
Python
from dataclasses import dataclass, field
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from random import Random
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from typing import Any, Callable, Optional
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from ..coaching import BaseCurriculum, ScalarAttributeDefinition
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from ..factory import ProceduralDataset, register_dataset
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from .board_format import ARC_PROMPT_TEMPLATE, BoardFormattingOptions, format_board, format_board_pair, parse_board
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RNG_DIFFICULTY_LEVELS = [0.0, 0.025, 0.05, 0.075, 0.1, 0.125, 0.15, 0.2]
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RNG_DIFFICULTY_RANGES = [
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(RNG_DIFFICULTY_LEVELS[i], RNG_DIFFICULTY_LEVELS[i + 1]) for i in range(len(RNG_DIFFICULTY_LEVELS) - 1)
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]
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PSO_DIFFICULTY_LEVELS = [0.05, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 1]
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PSO_DIFFICULTY_RANGES = [
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(PSO_DIFFICULTY_LEVELS[i], PSO_DIFFICULTY_LEVELS[i + 1]) for i in range(len(PSO_DIFFICULTY_LEVELS) - 1)
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]
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@dataclass
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class ReArcConfig:
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min_examples: int = 3 # minimum number of board pairs shown
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max_examples: int = 5 # maximum number of board pairs shown
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diff_lb: int = 0
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diff_ub: int = 0.2
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board_format_opts: BoardFormattingOptions = field(default_factory=lambda: BoardFormattingOptions())
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seed: Optional[int] = None
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size: int = 500
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rng_difficulty_ranges: list[tuple[float, float]] = field(default_factory=lambda: RNG_DIFFICULTY_RANGES)
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rng_difficulty_weights: list[float] = field(
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default_factory=lambda: [1 / len(RNG_DIFFICULTY_RANGES)] * len(RNG_DIFFICULTY_RANGES)
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)
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pso_difficulty_ranges: list[tuple[float, float]] = field(default_factory=lambda: PSO_DIFFICULTY_RANGES)
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pso_difficulty_weights: list[float] = field(
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default_factory=lambda: [1 / len(PSO_DIFFICULTY_RANGES)] * len(PSO_DIFFICULTY_RANGES)
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)
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def validate(self):
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assert self.min_examples > 0, "min_examples must be positive"
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assert self.min_examples <= self.max_examples, "min_examples must be <= max_examples"
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assert self.diff_lb <= self.diff_ub, "diff_lb must be <= diff_ub."
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assert self.size > 0, "Size of dataset must be positive."
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class ReArcDataset(ProceduralDataset):
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def __init__(self, config: ReArcConfig):
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super().__init__(config=config, seed=config.seed, size=config.size)
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self.board_format_opts = config.board_format_opts
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self._prompt_templates = ARC_PROMPT_TEMPLATE
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self.diff_lb = config.diff_lb
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self.diff_ub = config.diff_ub
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# lazy import of re-arc dsl & generators
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from .rearc_utils import generators
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from .rearc_utils.utils import get_generators, get_pso_difficulty
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self._generators = get_generators(generators)
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self.get_pso_difficulty = get_pso_difficulty
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@staticmethod
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def get_rng_difficulty(rng: Random) -> float:
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if not hasattr(rng, "difficulty_samples"):
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return 0.0
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samples = rng.difficulty_samples
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avg = sum(samples) / len(samples) if samples else 0.0
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rng.difficulty_samples = []
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return avg
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def __len__(self) -> int:
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return self.size
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def format_rearc_input(self, rng: Random, task: dict, generator: Callable) -> str:
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"""
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Format a ReArc task input with multiple examples and test input.
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"""
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num_examples = rng.randint(self.config.min_examples, self.config.max_examples)
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examples = [
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format_board_pair(
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i + 1, generator(rng, self.diff_lb, self.diff_ub), formatting_options=self.config.board_format_opts
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)
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for i in range(num_examples)
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]
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examples = "".join(examples)
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input_grid = format_board(task["input"], self.board_format_opts)
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return self._prompt_templates.format(examples=examples, input_grid=input_grid)
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def __getitem__(self, idx: int) -> dict:
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"""
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Generate a single ReArc task
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"""
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rng = Random(self.seed + idx)
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pso_difficulty_range = rng.choices(
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self.config.pso_difficulty_ranges, weights=self.config.pso_difficulty_weights, k=1
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)[0]
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while True:
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task_id = rng.choice(list(self._generators.keys()))
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generator = self._generators[task_id]
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difficulty_range = rng.choices(
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self.config.rng_difficulty_ranges, weights=self.config.rng_difficulty_weights, k=1
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)[0]
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task = generator(rng, difficulty_range[0], difficulty_range[1])
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pso_difficulty = self.get_pso_difficulty(task)
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if (pso_difficulty_range[0] <= pso_difficulty) and (pso_difficulty <= pso_difficulty_range[1]):
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break
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rng_difficulty = self.get_rng_difficulty(rng)
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input_prompt = self.format_rearc_input(rng, task, generator)
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answer = format_board(task["output"], self.board_format_opts)
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return {
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"question": input_prompt,
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"answer": answer,
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"metadata": {
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"input": task["input"],
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"output": task["output"],
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"task_id": task_id,
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"rng": rng_difficulty,
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"pso": pso_difficulty,
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"difficulty": {
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"rng_difficulty": self.config.rng_difficulty_weights,
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"pso_difficulty": self.config.pso_difficulty_weights,
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},
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},
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}
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def score_answer(self, answer: str, entry: dict[str, Any]) -> float:
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reward = 0.0
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metadata = entry["metadata"]
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if answer is not None:
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try:
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answer_board = parse_board(answer, self.board_format_opts)
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if answer_board == metadata["output"]:
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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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class ReArcCurriculum(BaseCurriculum):
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def __init__(self):
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super().__init__(ReArcCurriculum.__name__, ReArcConfig)
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self._define_attributes(
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ScalarAttributeDefinition(
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name="pso_difficulty",
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field_name="pso_difficulty_weights",
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description="The range of PSO difficulty for the Arc problem",
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levels=[
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[1, 0, 0, 0, 0, 0, 0, 0], # only sample/generate the easiest tasks wrs PSO difficulty
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[0, 1, 0, 0, 0, 0, 0, 0],
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[0, 0, 1, 0, 0, 0, 0, 0],
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[0, 0, 0, 1, 0, 0, 0, 0],
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[0, 0, 0, 0, 1, 0, 0, 0],
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[0, 0, 0, 0, 0, 1, 0, 0],
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[0, 0, 0, 0, 0, 0, 1, 0],
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[0, 0, 0, 0, 0, 0, 0, 1],
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], # only sample/generate the hardest tasks PSO difficulty
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),
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ScalarAttributeDefinition(
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name="rng_difficulty",
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field_name="rng_difficulty_weights",
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description="The range of RNG difficulty for the Arc problem",
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levels=[
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[1, 0, 0, 0, 0, 0, 0, 0], # only sample/generate the easiest tasks wrs RNG difficulty
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[0, 1, 0, 0, 0, 0, 0, 0],
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[0, 0, 1, 0, 0, 0, 0, 0],
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[0, 0, 0, 1, 0, 0, 0, 0],
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[0, 0, 0, 0, 1, 0, 0, 0],
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[0, 0, 0, 0, 0, 1, 0, 0],
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[0, 0, 0, 0, 0, 0, 1, 0],
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[0, 0, 0, 0, 0, 0, 0, 1],
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], # only sample/generate the hardest tasks wrs RNG difficulty
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),
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)
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register_dataset("rearc", ReArcDataset, ReArcConfig, ReArcCurriculum)
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