mirror of
https://github.com/open-thought/reasoning-gym.git
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* 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
154 lines
5.7 KiB
Python
154 lines
5.7 KiB
Python
"""Tests for Group Anagrams questions generation"""
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import json
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import pytest
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from reasoning_gym.algorithmic.group_anagrams import GroupAnagramsConfig, GroupAnagramsCurriculum, GroupAnagramsDataset
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def test_group_anagrams_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 = GroupAnagramsConfig(min_anagram_groups=-1) # Negative not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = GroupAnagramsConfig(min_anagram_groups=0) # Zero not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = GroupAnagramsConfig(min_anagram_groups=5, max_anagram_groups=4) # Min > Max not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = GroupAnagramsConfig(min_words_per_group=-1) # Negative not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = GroupAnagramsConfig(min_words_per_group=0) # Zero not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = GroupAnagramsConfig(min_words_per_group=5, max_words_per_group=4) # Min > Max not allowed
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config.validate() # Min > Max not allowed
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def test_group_anagrams_dataset_deterministic():
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"""Test that dataset generates same items with same seed"""
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config = GroupAnagramsConfig(seed=42, size=10)
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dataset1 = GroupAnagramsDataset(config)
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dataset2 = GroupAnagramsDataset(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_group_anagrams_dataset_items():
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"""Test basic properties of generated items"""
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config = GroupAnagramsConfig(max_anagram_groups=5, max_words_per_group=3, size=10, seed=42)
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dataset = GroupAnagramsDataset(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 "words" in item["metadata"]
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assert "solution" in item["metadata"]
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words = item["metadata"]["words"]
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solution = item["metadata"]["solution"]
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# Verify list dimensions
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assert len(words) >= len(solution)
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assert len(solution) <= 5
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assert all(len(group) <= 3 for group in solution)
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def test_group_anagrams_dataset_iteration():
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"""Test that iteration respects dataset size"""
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config = GroupAnagramsConfig(size=5, seed=42)
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dataset = GroupAnagramsDataset(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_group_anagrams_answer():
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"""Test the _group_anagrams method"""
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config = GroupAnagramsConfig(seed=42)
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dataset = GroupAnagramsDataset(config)
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# General use case
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words = ["eat", "tea", "tan", "ate", "nat", "bat"]
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correct = [["ate", "eat", "tea"], ["bat"], ["nat", "tan"]]
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assert json.dumps(dataset._group_anagrams(words)) == json.dumps(correct)
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# Single word
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words = ["a"]
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correct = [["a"]]
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assert json.dumps(dataset._group_anagrams(words)) == json.dumps(correct)
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# Empty list
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words = []
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correct = []
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assert json.dumps(dataset._group_anagrams(words)) == json.dumps(correct)
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def test_group_anagrams_score_answer():
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"""Test the score_answer method"""
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config = GroupAnagramsConfig(seed=42)
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dataset = GroupAnagramsDataset(config)
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# Verify the scoring function is permutation invariant
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answer = json.dumps([["bat"], ["nat", "tan"], ["ate", "eat", "tea"]])
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item = {"metadata": {"solution": [["ate", "eat", "tea"], ["bat"], ["nat", "tan"]]}}
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assert dataset.score_answer(answer, item) == 1
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# Verify the score is 0.01 when incorrect
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answer = json.dumps([["ate", "eat"], ["bat", "tea"], ["nat", "tan"]])
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item = {"metadata": {"solution": [["ate", "eat", "tea"], ["bat"], ["nat", "tan"]]}}
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assert dataset.score_answer(answer, item) == 0.01
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# Verify the score is 0 when answer is None
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answer = None
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item = {"metadata": {"solution": [["ate", "eat", "tea"], ["bat"], ["nat", "tan"]]}}
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assert dataset.score_answer(answer, item) == 0
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# Verify the score is 0 when answer is malformed JSON
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answer = '["ate", "eat", "tea"], ["bat"], ["nat", "tan"]'
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item = {"metadata": {"solution": [["ate", "eat", "tea"], ["bat"], ["nat", "tan"]]}}
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assert dataset.score_answer(answer, item) == 0
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def test_group_anagrams_curriculum():
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curriculum = GroupAnagramsCurriculum()
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base_value = {"size": 150, "seed": 1}
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base_cfg: GroupAnagramsConfig = 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_anagram_groups == 5 and base_cfg.max_anagram_groups == 10
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assert base_cfg.min_words_per_group == 2 and base_cfg.max_words_per_group == 2
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# test incrementing attribute levels
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curriculum.increment_attr_level("anagram_groups")
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curriculum.increment_attr_level("words_per_group")
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increased_cfg = curriculum.generate_configuration(base_value)
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assert increased_cfg.min_anagram_groups == 5 and increased_cfg.max_anagram_groups == 50
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assert increased_cfg.min_words_per_group == 2 and increased_cfg.max_words_per_group == 5
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# test decrementing attribute level partially
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curriculum.decrement_attr_level("anagram_groups")
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partially_decreased_cfg = curriculum.generate_configuration(base_value)
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assert partially_decreased_cfg.min_anagram_groups == 5 and partially_decreased_cfg.max_anagram_groups == 10
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assert partially_decreased_cfg.min_words_per_group == 2 and partially_decreased_cfg.max_words_per_group == 5
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