mirror of
https://github.com/open-thought/reasoning-gym.git
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116 lines
3.9 KiB
Python
116 lines
3.9 KiB
Python
import pytest
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from reasoning_gym.cognition.number_sequences import (
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NumberSequenceConfig,
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NumberSequenceCurriculum,
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NumberSequenceDataset,
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Operation,
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PatternRule,
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)
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def test_sequence_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 = NumberSequenceConfig(min_terms=3) # Too few terms
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config.validate()
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with pytest.raises(AssertionError):
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config = NumberSequenceConfig(min_terms=6, max_terms=5)
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config.validate()
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with pytest.raises(AssertionError):
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config = NumberSequenceConfig(min_value=100, max_value=0)
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config.validate()
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def test_pattern_rule():
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"""Test pattern rule application"""
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# Test simple addition
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rule = PatternRule([Operation.ADD], [2])
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assert rule.apply([1, 3], 1) == 5
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# Test composition
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rule = PatternRule([Operation.DOUBLE, Operation.ADD], [0, 3])
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assert rule.apply([1, 4], 1) == 11 # (4 * 2) + 3
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# Test rule composition
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rule1 = PatternRule([Operation.DOUBLE], [0]) # Double the number
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rule2 = PatternRule([Operation.ADD], [3]) # Add 3
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composed = PatternRule.compose([rule1, rule2])
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assert composed.apply([1, 4], 1) == 11 # (4 * 2) + 3
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def test_sequence_dataset_deterministic():
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"""Test that dataset generates same items with same seed"""
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config = NumberSequenceConfig(seed=42, size=10)
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dataset1 = NumberSequenceDataset(config)
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dataset2 = NumberSequenceDataset(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_sequence_dataset_items():
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"""Test basic properties of generated items"""
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config = NumberSequenceConfig(min_terms=4, max_terms=6, max_complexity=2, size=50, seed=42)
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dataset = NumberSequenceDataset(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 sequence format
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question = item["question"]
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assert question.endswith(", ?")
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terms = [int(x) for x in question[:-3].split(", ")]
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assert len(terms) >= config.min_terms
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assert len(terms) <= config.max_terms
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def test_sequence_dataset_iteration():
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"""Test that iteration respects dataset size"""
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config = NumberSequenceConfig(size=5, seed=42)
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dataset = NumberSequenceDataset(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_number_sequence_curriculum():
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"""Test the number sequence curriculum functionality"""
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curriculum = NumberSequenceCurriculum()
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# Test with custom base values
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base_value = {"size": 150, "seed": 42}
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# Test basic configuration generation
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base_cfg: NumberSequenceConfig = curriculum.generate_configuration(base_value)
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assert base_cfg.seed == 42
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assert base_cfg.size == 150
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assert base_cfg.max_complexity == 1 # Default level (0) corresponds to complexity 1
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# Test attribute level increment
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curriculum.increment_attr_level("max_complexity")
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increased_cfg = curriculum.generate_configuration(base_value)
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assert increased_cfg.max_complexity == 2 # Level 1 corresponds to complexity 2
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# Test attribute level increment again
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curriculum.increment_attr_level("max_complexity")
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increased_cfg = curriculum.generate_configuration(base_value)
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assert increased_cfg.max_complexity == 3 # Level 2 corresponds to complexity 3
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# Test that other parameters remain unchanged
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assert increased_cfg.seed == 42
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assert increased_cfg.size == 150
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# Test attribute level decrement
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curriculum.decrement_attr_level("max_complexity")
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decreased_cfg = curriculum.generate_configuration(base_value)
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assert decreased_cfg.max_complexity == 2 # Back to level 1, complexity 2
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