reasoning-gym/reasoning_gym/arithmetic/chain_sum.py
2025-01-23 22:27:48 +01:00

160 lines
5.2 KiB
Python

import random
from dataclasses import dataclass
from typing import Optional
@dataclass
class ChainSumConfig:
"""Configuration for chain sum task generation"""
min_terms: int = 2
max_terms: int = 6
min_digits: int = 1
max_digits: int = 4
allow_negation: bool = False
seed: Optional[int] = None
size: int = 500
def validate(self):
"""Validate configuration parameters"""
assert self.min_terms > 0, "min_terms must be positive"
assert self.max_terms >= self.min_terms, "max_terms must be >= min_terms"
assert self.min_digits > 0, "min_digits must be positive"
assert self.max_digits >= self.min_digits, "max_digits must be >= min_digits"
# Validate digit ranges make sense
if self.min_digits > 1:
assert 10 ** (self.min_digits - 1) >= 1, "min_digits would result in invalid number range"
class ChainSum:
"""Generates simple arithmetic tasks using only + and - operators"""
def __init__(self, config: ChainSumConfig):
self.config = config
self.config.validate()
# Generate base seed if none provided
self.seed = config.seed if config.seed is not None else random.randint(0, 2**32)
def __len__(self) -> int:
return self.config.size
def __getitem__(self, idx: int) -> dict:
"""Generate a single chain sum task
Args:
idx: Index of the item to generate
Returns:
dict with keys:
- question: str, the formatted arithmetic expression
- answer: str, the ground truth result
- metadata: dict with generation parameters
"""
# Create deterministic RNG from base seed and idx
item_rng = random.Random(self.seed + idx)
num_terms = item_rng.randint(self.config.min_terms, self.config.max_terms)
num_digits = item_rng.randint(self.config.min_digits, self.config.max_digits)
# Calculate value ranges based on number of digits
min_value = 0 if num_digits == 1 else 10 ** (num_digits - 1) # Special case for 1 digit
max_value = (10**num_digits) - 1 # e.g., 999 for 3 digits
expression, result = self._generate_task(item_rng, num_terms, min_value, max_value)
return {
"question": f"{expression} =",
"answer": str(result),
"metadata": {
"num_terms": num_terms,
"num_digits": num_digits,
"expression": expression,
},
}
def __iter__(self):
"""Make the dataset iterable"""
self._current_idx = 0
return self
def __next__(self):
"""Get next item in iteration"""
if self._current_idx >= self.config.size:
raise StopIteration
item = self[self._current_idx]
self._current_idx += 1
return item
def _generate_task(self, rng: random.Random, num_terms: int, min_value: int, max_value: int) -> tuple[str, int]:
"""Generate a chain sum task
Args:
rng: Random number generator
num_terms: Number of terms in the expression
min_value: Minimum value for generated numbers
max_value: Maximum value for generated numbers
Returns:
Tuple of (expression string, result integer)
"""
if self.config.allow_negation:
# Allow both positive and negative numbers in the range
constants = [rng.randint(-max_value, max_value) for _ in range(num_terms)]
else:
# Only positive numbers
constants = [rng.randint(min_value, max_value) for _ in range(num_terms)]
operators = [rng.choice(["+", "-"]) for _ in range(num_terms - 1)]
# Build expression and compute result
expression_parts = []
result = constants[0]
expression_parts.append(str(constants[0]))
for i, op in enumerate(operators):
c = constants[i + 1]
expression_parts.append(op)
expression_parts.append(str(c))
if op == "+":
result += c
else: # op == "-"
result -= c
expression = " ".join(expression_parts)
return expression, result
def chain_sum_dataset(
min_terms: int = 2,
max_terms: int = 6,
min_digits: int = 1,
max_digits: int = 4,
allow_negation: bool = False,
seed: Optional[int] = None,
size: int = 500,
) -> ChainSum:
"""Create a ChainSum dataset with the given configuration.
Args:
min_terms: Minimum number of terms in expressions
max_terms: Maximum number of terms in expressions
min_digits: Minimum number of digits in numbers
max_digits: Maximum number of digits in numbers
allow_negation: Whether to allow negative numbers
seed: Random seed for reproducibility
size: Virtual size of the dataset
Returns:
ChainSum: Configured dataset instance
"""
config = ChainSumConfig(
min_terms=min_terms,
max_terms=max_terms,
min_digits=min_digits,
max_digits=max_digits,
allow_negation=allow_negation,
seed=seed,
size=size,
)
return ChainSum(config)