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140 lines
4.3 KiB
Python
140 lines
4.3 KiB
Python
"""Tests for Binary Matrix questions generation"""
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import pytest
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from reasoning_gym.algorithmic.rotten_oranges import RottenOrangesConfig, RottenOrangesCurriculum, RottenOrangesDataset
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def test_rotten_oranges_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 = RottenOrangesConfig(max_n=-1) # Negative not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = RottenOrangesConfig(max_n=0) # Zero not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = RottenOrangesConfig(min_n=-1) # Negative not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = RottenOrangesConfig(min_n=0) # Zero not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = RottenOrangesConfig(p_oranges=0) # <= 0 not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = RottenOrangesConfig(p_oranges=1.01) # > 1 not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = RottenOrangesConfig(p_rotten=0) # <= 0 not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = RottenOrangesConfig(p_rotten=1.01) # > 1 not allowed
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config.validate()
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def test_rotten_oranges_dataset_deterministic():
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"""Test that dataset generates same items with same seed"""
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config = RottenOrangesConfig(seed=42, size=10)
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dataset1 = RottenOrangesDataset(config)
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dataset2 = RottenOrangesDataset(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_rotten_oranges_dataset_items():
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"""Test basic properties of generated items"""
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config = RottenOrangesConfig(min_n=10, max_n=15, size=10, seed=42)
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dataset = RottenOrangesDataset(config)
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for i in range(len(dataset)):
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item = dataset[i]
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# Check item structure
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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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# Check metadata
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assert "matrix" in item["metadata"]
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assert "solution" in item["metadata"]
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matrix = item["metadata"]["matrix"]
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# Verify dimensions
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assert config.min_n <= len(matrix) <= config.max_n
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assert all(config.min_n <= len(row) <= config.max_n for row in matrix)
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for r in range(len(matrix)):
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for c in range(len(matrix[0])):
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assert matrix[r][c] in [0, 1, 2]
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def test_rotten_oranges_dataset_iteration():
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"""Test that iteration respects dataset size"""
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config = RottenOrangesConfig(size=5, seed=42)
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dataset = RottenOrangesDataset(config)
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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 items
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assert items == list(dataset)
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def test_rotten_oranges_answer():
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"""Test the _get_distances method"""
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config = RottenOrangesConfig(seed=42)
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dataset = RottenOrangesDataset(config)
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# All oranges are rotten
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matrix = [
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[2, 2, 2],
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[2, 2, 2],
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[2, 2, 2],
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]
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assert dataset._get_answer(matrix) == 0
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# All oranges are healthy
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matrix = [
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[1, 1, 1],
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[1, 1, 1],
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[1, 1, 1],
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]
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assert dataset._get_answer(matrix) == -1
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# 1 shot example
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matrix = [
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[2, 1, 1],
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[1, 1, 0],
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[0, 1, 1],
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]
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assert dataset._get_answer(matrix) == 4
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def test_rotten_oranges_curriculum():
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curriculum = RottenOrangesCurriculum()
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base_value = {"size": 150, "seed": 1}
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base_cfg: RottenOrangesConfig = 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_n == 10 and base_cfg.max_n == 10
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# test incrementing attribute levels
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curriculum.increment_attr_level("n")
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increased_cfg = curriculum.generate_configuration(base_value)
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assert increased_cfg.min_n == 10 and increased_cfg.max_n == 25
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# test decrementing attribute level for n again
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curriculum.decrement_attr_level("n")
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partially_decreased_cfg = curriculum.generate_configuration(base_value)
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assert partially_decreased_cfg.min_n == 10 and partially_decreased_cfg.max_n == 10
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