reasoning-gym/tests/test_list_functions.py
2025-02-21 00:37:29 -06:00

84 lines
2.5 KiB
Python

from random import Random
import pytest
from reasoning_gym.induction.list_functions import ListFunctionsDataset, ListFunctionsDatasetConfig
def test_list_functions_config_validation():
"""Test that config validation works"""
config = ListFunctionsDatasetConfig(size=-1)
with pytest.raises(AssertionError):
config.validate()
def test_list_functions_deterministic():
"""Test that dataset generates same items with same seed"""
config = ListFunctionsDatasetConfig(seed=42, size=10)
dataset1 = ListFunctionsDataset(config)
dataset2 = ListFunctionsDataset(config)
for i in range(len(dataset1)):
assert dataset1[i] == dataset2[i]
def test_list_functions_items():
"""Test basic properties of generated items"""
config = ListFunctionsDatasetConfig(size=50, seed=42)
dataset = ListFunctionsDataset(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_list_functions_iteration():
"""Test that iteration respects dataset size"""
config = ListFunctionsDatasetConfig(size=5, seed=42) # Small size for testing
dataset = ListFunctionsDataset(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_list_functions_generators():
"""Test generator loading and access"""
config = ListFunctionsDatasetConfig()
dataset = ListFunctionsDataset(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)
for _ in range(10):
x = generator(rng)
assert isinstance(x, dict)
i += 1