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84 lines
2.7 KiB
Python
84 lines
2.7 KiB
Python
"""Tests for spell backward task generation"""
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import pytest
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from reasoning_gym.algorithmic.spell_backward import SpellBackwardConfig, SpellBackwardCurriculum, SpellBackwardDataset
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def test_spell_backward_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 = SpellBackwardConfig(min_word_len=0)
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config.validate()
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with pytest.raises(AssertionError):
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config = SpellBackwardConfig(min_word_len=4, max_word_len=3)
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config.validate()
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def test_spell_backward_dataset_deterministic():
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"""Test that dataset generates same items with same seed"""
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config = SpellBackwardConfig(seed=42, size=10)
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dataset1 = SpellBackwardDataset(config)
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dataset2 = SpellBackwardDataset(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_spell_backward_dataset_items():
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"""Test basic properties of generated items"""
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config = SpellBackwardConfig(min_word_len=3, size=10, seed=42)
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dataset = SpellBackwardDataset(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 "word" in item["metadata"]
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assert "word_len" in item["metadata"]
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# Verify word length constraint
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word = item["metadata"]["word"]
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assert len(word) >= config.min_word_len
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# Verify answer is correct
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assert item["answer"] == word[::-1]
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def test_spell_backward_dataset_iteration():
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"""Test that iteration respects dataset size"""
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config = SpellBackwardConfig(size=5, seed=42)
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dataset = SpellBackwardDataset(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_spell_backward_curriculum():
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curriculum = SpellBackwardCurriculum()
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base_value = {"size": 150, "seed": 1}
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base_cfg: SpellBackwardConfig = 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_word_len == 3 and base_cfg.max_word_len == 3
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# test incrementing attribute levels
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curriculum.increment_attr_level("word_len")
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increased_cfg = curriculum.generate_configuration(base_value)
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assert increased_cfg.min_word_len == 3 and increased_cfg.max_word_len == 4
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# test decrementing attribute levels
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curriculum.decrement_attr_level("word_len")
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partially_decreased_cfg = curriculum.generate_configuration(base_value)
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assert partially_decreased_cfg.min_word_len == 3 and partially_decreased_cfg.max_word_len == 3
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