mirror of
https://github.com/open-thought/reasoning-gym.git
synced 2026-04-19 12:58:07 +00:00
dced3bfc45
* init * fix tests * unify codeio * filtered for libraries not present in reasoning-gym * fix more bounds * puzzle24 * knight swap curriculum * fix number sorting * fix attributes * add validation of config in creation of dataset * dry run for instantiating and validating the datasets * remove unused imports * fix curriculum tests to reference newly updated attribute names
147 lines
5 KiB
Python
147 lines
5 KiB
Python
from functools import reduce
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from math import gcd
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import pytest
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from reasoning_gym.arithmetic import GCDConfig, GCDCurriculum, GCDDataset
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def test_gcd_config_validation():
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"""Test that invalid configs raise appropriate errors"""
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with pytest.raises(AssertionError):
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config = GCDConfig(min_numbers=1) # Should be >= 2
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config.validate()
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with pytest.raises(AssertionError):
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config = GCDConfig(min_numbers=3, max_numbers=2) # max should be >= min
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config.validate()
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with pytest.raises(AssertionError):
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config = GCDConfig(min_value=0) # Should be positive
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config.validate()
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with pytest.raises(AssertionError):
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config = GCDConfig(min_value=100, max_value=50) # max should be > min
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config.validate()
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def test_gcd_deterministic():
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"""Test that dataset generates same items with same seed"""
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config = GCDConfig(seed=42, size=10)
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dataset1 = GCDDataset(config)
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dataset2 = GCDDataset(config)
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for i in range(len(dataset1)):
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assert dataset1[i] == dataset2[i]
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def test_gcd_items():
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"""Test basic properties of generated items"""
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config = GCDConfig(min_numbers=2, max_numbers=4, min_value=1, max_value=100, size=50, seed=42)
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dataset = GCDDataset(config)
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for i in range(len(dataset)):
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item = dataset[i]
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assert isinstance(item, dict)
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assert "question" in item
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assert "answer" in item
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assert "metadata" in item
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# Verify the numbers and result are in metadata
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metadata = item["metadata"]
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assert "numbers" in metadata
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assert "result" in metadata
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# Verify the numbers are within configured range
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numbers = metadata["numbers"]
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assert all(config.min_value <= n <= config.max_value for n in numbers)
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assert config.min_numbers <= len(numbers) <= config.max_numbers
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# Verify the GCD calculation is correct
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result = metadata["result"]
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assert str(result) == item["answer"]
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assert result == reduce(gcd, numbers)
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def test_gcd_number_ranges():
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"""Test that generated numbers respect value constraints"""
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config = GCDConfig(min_numbers=2, max_numbers=2, min_value=50, max_value=100, size=20, seed=42)
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dataset = GCDDataset(config)
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for i in range(len(dataset)):
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item = dataset[i]
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numbers = item["metadata"]["numbers"]
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assert all(50 <= n <= 100 for n in numbers)
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def test_gcd_iteration():
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"""Test that iteration works correctly"""
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config = GCDConfig(size=5, seed=42)
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dataset = GCDDataset(config)
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# Test manual iteration
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items = []
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for item in dataset:
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items.append(item)
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assert len(items) == config.size
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# Test list conversion
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items = list(dataset)
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assert len(items) == config.size
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# Test multiple iterations yield same results
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first_items = list(dataset)
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second_items = list(dataset)
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assert first_items == second_items
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def test_gcd_special_cases():
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"""Test some special GCD cases"""
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config = GCDConfig(min_numbers=2, max_numbers=2, min_value=1, max_value=100, size=100, seed=42)
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dataset = GCDDataset(config)
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# Track if we see some interesting GCD cases
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seen_gcd_1 = False # Coprime numbers
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seen_large_gcd = False # GCD > 1
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for i in range(len(dataset)):
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item = dataset[i]
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result = int(item["answer"])
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if result == 1:
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seen_gcd_1 = True
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if result > 1:
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seen_large_gcd = True
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# With enough samples, we should see both coprime and non-coprime numbers
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assert seen_gcd_1, "Expected to see some coprime numbers (GCD=1)"
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assert seen_large_gcd, "Expected to see some non-coprime numbers (GCD>1)"
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def test_gcd_curriculum():
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"""Test that curriculum generates correct items"""
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curriculum = GCDCurriculum()
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base_value = {"size": 150, "seed": 1}
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base_cfg: GCDConfig = curriculum.generate_configuration(base_value)
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assert base_cfg.seed == 1
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assert base_cfg.size == 150
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assert base_cfg.min_numbers == 2 and base_cfg.max_numbers == 2
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assert base_cfg.min_value == 100 and base_cfg.max_value == 1000
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curriculum.increment_attr_level("num_terms")
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curriculum.increment_attr_level("value")
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increased_cfg = curriculum.generate_configuration(base_value)
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assert increased_cfg.min_numbers == 2 and increased_cfg.max_numbers == 3
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assert increased_cfg.min_value == 100 and increased_cfg.max_value == 10000
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curriculum.increment_attr_level("num_terms")
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curriculum.increment_attr_level("value")
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increased_cfg = curriculum.generate_configuration(base_value)
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assert increased_cfg.min_numbers == 2 and increased_cfg.max_numbers == 4
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assert increased_cfg.min_value == 100 and increased_cfg.max_value == 100000
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curriculum.decrement_attr_level("num_terms")
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curriculum.decrement_attr_level("value")
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decreased_cfg = curriculum.generate_configuration(base_value)
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assert decreased_cfg.min_numbers == 2 and decreased_cfg.max_numbers == 3
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assert decreased_cfg.min_value == 100 and decreased_cfg.max_value == 10000
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