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
5.4 KiB
Python
154 lines
5.4 KiB
Python
"""Tests for Number Format questions generation"""
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import pytest
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from reasoning_gym.arithmetic.number_format import NumberFormatConfig, NumberFormatCurriculum, NumberFormatDataset
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def test_number_format_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 = NumberFormatConfig(min_num_candidates=0) # Zero not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = NumberFormatConfig(min_num_candidates=1) # One not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = NumberFormatConfig(max_num_candidates=5, min_num_candidates=6) # min > max
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config.validate()
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with pytest.raises(AssertionError):
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config = NumberFormatConfig(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 = NumberFormatConfig(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 = NumberFormatConfig(min_n=10, max_n=5) # min > max
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config.validate()
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with pytest.raises(AssertionError):
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config = NumberFormatConfig(max_delta=-1) # Negative not allowed
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config.validate()
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with pytest.raises(AssertionError):
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config = NumberFormatConfig(max_delta=0) # Zero not allowed
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config.validate()
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def test_number_format_dataset_deterministic():
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"""Test that dataset generates same items with same seed"""
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config = NumberFormatConfig(seed=42, size=10)
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dataset1 = NumberFormatDataset(config)
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dataset2 = NumberFormatDataset(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_number_format_dataset_items():
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"""Test basic properties of generated items"""
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config = NumberFormatConfig(min_n=1_000, max_n=10_000, max_delta=1, size=10, seed=42)
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dataset = NumberFormatDataset(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 "candidates" in item["metadata"]
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assert "formatted_candidates" in item["metadata"]
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assert "size" in item["metadata"]
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assert "solution" in item["metadata"]
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candidates = item["metadata"]["candidates"]
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formatted_candidates = item["metadata"]["formatted_candidates"]
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size = item["metadata"]["size"]
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solution = item["metadata"]["solution"]
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# Verify values
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assert len(candidates) >= 2
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assert all(999 <= c <= 10_001 for c in candidates) # boundaries +- delta
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assert len(candidates) == len(formatted_candidates)
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assert size in ["largest", "smallest"]
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assert solution in candidates
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def test_number_format_dataset_iteration():
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"""Test that iteration respects dataset size"""
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config = NumberFormatConfig(size=5, seed=42)
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dataset = NumberFormatDataset(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_format_answer():
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"""Verify the solution scoring"""
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config = NumberFormatConfig(size=5, seed=42)
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dataset = NumberFormatDataset(config)
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entry = {"metadata": {"solution": 54245.32}}
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# Correct answer (plain)
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model_answer = "54245.32"
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assert dataset.score_answer(model_answer, entry) == 1.0
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# Correct answer (English)
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model_answer = "54,245.32"
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assert dataset.score_answer(model_answer, entry) == 1.0
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# Correct answer (scientific)
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assert dataset.score_answer("5.424532e+04", entry) == 1.0
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# Incorrect answer (diff larger than 1e-2)
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model_answer = "54245.9"
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assert dataset.score_answer(model_answer, entry) == 0.0
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# Answer is null
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model_answer = None
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assert dataset.score_answer(model_answer, entry) == 0.0
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# Answer is unparsable
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model_answer = "test"
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assert dataset.score_answer(model_answer, entry) == 0.0
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def test_number_format_curriculum():
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curriculum = NumberFormatCurriculum()
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base_value = {"size": 150, "seed": 1}
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base_cfg: NumberFormatConfig = 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_num_candidates == 5 and base_cfg.max_num_candidates == 25
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assert base_cfg.min_n == 1000 and base_cfg.max_n == 100_000
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assert base_cfg.max_delta == 1e1
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# test incrementing attribute levels
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curriculum.increment_attr_level("num_candidates")
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curriculum.increment_attr_level("n")
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curriculum.increment_attr_level("max_delta")
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increased_cfg = curriculum.generate_configuration(base_value)
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assert increased_cfg.min_num_candidates == 5 and increased_cfg.max_num_candidates == 100
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assert increased_cfg.min_n == 1000 and increased_cfg.max_n == 1_000_000
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assert increased_cfg.max_delta == 1e0
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# test decrementing attribute level
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curriculum.decrement_attr_level("num_candidates")
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partially_decreased_cfg = curriculum.generate_configuration(base_value)
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assert partially_decreased_cfg.min_num_candidates == 5 and partially_decreased_cfg.max_num_candidates == 25
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assert partially_decreased_cfg.min_n == 1000 and partially_decreased_cfg.max_n == 1_000_000
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assert partially_decreased_cfg.max_delta == 1e0
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