mirror of
https://github.com/open-thought/reasoning-gym.git
synced 2026-04-19 12:58:07 +00:00
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
94 lines
3 KiB
Python
94 lines
3 KiB
Python
"""Word reversal task generator"""
|
|
|
|
import re
|
|
from dataclasses import dataclass
|
|
from random import Random
|
|
from typing import Optional
|
|
|
|
from ..coaching import BaseCurriculum, RangeAttributeDefinition
|
|
from ..data import read_data_file
|
|
from ..factory import ProceduralDataset, register_dataset
|
|
|
|
QUESTION_TEMPLATE = """Solve the following problem.
|
|
|
|
Provide you answer as a comma-separated list of words with a space after the comma.
|
|
|
|
Reverse this list of words: {words}
|
|
"""
|
|
|
|
|
|
@dataclass
|
|
class WordSequenceReversalConfig:
|
|
"""Configuration for word sequence reversal task generation"""
|
|
|
|
min_words: int = 3 # Minimum words in list
|
|
max_words: int = 8 # Maximum words in list
|
|
seed: Optional[int] = None
|
|
size: int = 500 # Virtual dataset size
|
|
|
|
def validate(self) -> None:
|
|
"""Validate configuration parameters"""
|
|
assert self.min_words > 0, "min_words must be positive"
|
|
assert self.max_words >= self.min_words, "max_words must be >= min_words"
|
|
|
|
|
|
class WordSequenceReversalDataset(ProceduralDataset):
|
|
"""Generates word sequence reversal tasks from text spans"""
|
|
|
|
def __init__(self, config: WordSequenceReversalConfig):
|
|
super().__init__(config=config, seed=config.seed, size=config.size)
|
|
|
|
# Load and preprocess text
|
|
text = read_data_file("in_the_year_2889.txt")
|
|
# Extract words and clean them to contain only alphanumeric characters
|
|
self.words = [word for word in re.findall(r"\b\w+\b", text) if word.isalnum()]
|
|
|
|
def __getitem__(self, idx: int) -> dict:
|
|
"""Generate a single word reversal task"""
|
|
rng = Random(self.seed + idx)
|
|
|
|
# Select random words
|
|
num_words = min(
|
|
rng.randint(self.config.min_words, self.config.max_words),
|
|
len(self.words),
|
|
)
|
|
word_indices = rng.sample(range(len(self.words)), num_words)
|
|
words = [self.words[i] for i in word_indices]
|
|
|
|
# Create question and answer
|
|
words_str = ", ".join(words)
|
|
answer = ", ".join(reversed(words))
|
|
|
|
return {
|
|
"question": f"{QUESTION_TEMPLATE.format(words=words_str)}",
|
|
"answer": answer,
|
|
"metadata": {
|
|
"num_words": num_words,
|
|
"words": words,
|
|
"difficulty": {
|
|
"words": (self.config.min_words, self.config.max_words),
|
|
},
|
|
},
|
|
}
|
|
|
|
|
|
class WordSequenceReversalCurriculum(BaseCurriculum):
|
|
def __init__(self):
|
|
super().__init__(WordSequenceReversalCurriculum.__name__, WordSequenceReversalConfig)
|
|
|
|
# Define attributes
|
|
self._define_attributes(
|
|
RangeAttributeDefinition(
|
|
name="words",
|
|
levels=[10, 50, 100, 500],
|
|
description="Number of words in the list",
|
|
lower_field_name="min_words",
|
|
upper_field_name="max_words",
|
|
ensure_interval=True,
|
|
),
|
|
)
|
|
|
|
|
|
register_dataset(
|
|
"word_sequence_reversal", WordSequenceReversalDataset, WordSequenceReversalConfig, WordSequenceReversalCurriculum
|
|
)
|