mirror of
https://github.com/open-thought/reasoning-gym.git
synced 2026-04-19 12:58:07 +00:00
d9638df79c
* updated algorithmic datasets * added changes to symbolic and power * updated power function test
103 lines
3.1 KiB
Python
103 lines
3.1 KiB
Python
from random import Random
|
|
|
|
import pytest
|
|
|
|
from reasoning_gym.arithmetic.gsm_symbolic import GSMSymbolicDataset, GSMSymbolicDatasetConfig
|
|
|
|
|
|
def test_gsm_symbolic_config_validation():
|
|
"""Test that config validation works"""
|
|
config = GSMSymbolicDatasetConfig(size=-1)
|
|
with pytest.raises(AssertionError):
|
|
config.validate()
|
|
|
|
|
|
def test_gsm_symbolic_deterministic():
|
|
"""Test that dataset generates same items with same seed"""
|
|
config = GSMSymbolicDatasetConfig(seed=42, size=10)
|
|
dataset1 = GSMSymbolicDataset(config)
|
|
dataset2 = GSMSymbolicDataset(config)
|
|
|
|
for i in range(len(dataset1)):
|
|
assert dataset1[i] == dataset2[i]
|
|
|
|
|
|
def test_gsm_symbolic_items():
|
|
"""Test basic properties of generated items"""
|
|
config = GSMSymbolicDatasetConfig(size=100, seed=42)
|
|
dataset = GSMSymbolicDataset(config)
|
|
|
|
for i in range(len(dataset)):
|
|
item = dataset[i]
|
|
assert isinstance(item, dict)
|
|
assert "question" in item
|
|
assert "answer" in item
|
|
assert isinstance(item["question"], str)
|
|
assert isinstance(item["answer"], str)
|
|
|
|
|
|
def test_gsm_symbolic_iteration():
|
|
"""Test that iteration respects dataset size"""
|
|
config = GSMSymbolicDatasetConfig(size=5, seed=42) # Small size for testing
|
|
dataset = GSMSymbolicDataset(config)
|
|
|
|
# Test manual iteration
|
|
items = []
|
|
for item in dataset:
|
|
items.append(item)
|
|
assert len(items) == config.size, "Iterator should yield exactly size items"
|
|
|
|
# Test list conversion
|
|
items = list(dataset)
|
|
assert len(items) == config.size, "Iterator should yield exactly size items"
|
|
|
|
# Test multiple iterations
|
|
first_items = list(dataset)
|
|
second_items = list(dataset)
|
|
assert first_items == second_items, "Multiple iterations should yield same items"
|
|
|
|
|
|
def test_gsm_symbolic_generators():
|
|
"""Test generator loading and access"""
|
|
config = GSMSymbolicDatasetConfig()
|
|
dataset = GSMSymbolicDataset(config)
|
|
|
|
# Test lazy loading
|
|
assert dataset._generators is None
|
|
_ = dataset.generators # Access to trigger loading
|
|
assert dataset._generators is not None
|
|
|
|
# Test generator mapping
|
|
assert isinstance(dataset.generators, dict)
|
|
assert len(dataset.generators) > 0
|
|
i = 0
|
|
rng = Random(18)
|
|
for key in sorted(dataset.generators.keys()):
|
|
generator = dataset.generators[key]
|
|
assert callable(generator)
|
|
|
|
print(i, key)
|
|
answer_set = set()
|
|
question_set = set()
|
|
for j in range(10):
|
|
x = generator(rng, difficulty=1.0)
|
|
question_set.add(x["question"])
|
|
answer_set.add(x["answer"])
|
|
# if j == 123:
|
|
# print(f"[{j}] q: {x['question']}")
|
|
# print(f"a: {x['answer']}")
|
|
# print()
|
|
print(f"ok: q={len(question_set)}, a={len(answer_set)}")
|
|
|
|
i += 1
|
|
|
|
|
|
def test_gsm_symbolic_score_answer():
|
|
"""Test score answer function"""
|
|
config = GSMSymbolicDatasetConfig(size=100, seed=42)
|
|
dataset = GSMSymbolicDataset(config)
|
|
|
|
for i in range(len(dataset)):
|
|
item = dataset[i]
|
|
score = dataset.score_answer(item["answer"], item)
|
|
assert score == 1.0
|