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* added curriculum * readapted readme * corrected small errors * Delete eval/eval/r1/algorithmic/word_sorting.json * removed redundant argument * added spell * removed duplicated fit * changed config * added composite changes * added composite changes * updated yaml * added spell backward * updated read me * added qwen2.5 * added * Add files via upload * updated missing trainer func * updated curr * updated spell back * updated correctness score func * updated configs * added local evals * added updates * updated datasets * added fsdp to hf utility * added algorithmic qwen 3b yaml * updated read me * updated configs * added preappend token * updated with thinking token * updated test score board * resolved comments * added evaluation scripts * removed results from pr * added config * added partial reward scoring * added evaluation composites * added training configs * added games eval * added rubriks cube * resolved merge cinflicts * added games config * added latest eval configs * updated strucutre * Delete training/evaluations/eval_graphs_composite.yaml --------- Co-authored-by: joesharratt1229 <joesharrat1229@gmail.com>
176 lines
7 KiB
Python
176 lines
7 KiB
Python
"""Tests for number sorting task generation"""
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import pytest
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from reasoning_gym.algorithmic.number_sorting import NumberSortingConfig, NumberSortingCurriculum, NumberSortingDataset
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def test_number_sorting_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 = NumberSortingConfig(min_numbers=0)
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config.validate()
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with pytest.raises(AssertionError):
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config = NumberSortingConfig(min_numbers=10, max_numbers=5)
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config.validate()
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with pytest.raises(AssertionError):
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config = NumberSortingConfig(min_decimals=-1)
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config.validate()
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with pytest.raises(AssertionError):
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config = NumberSortingConfig(min_value=100, max_value=0)
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config.validate()
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def test_number_sorting_dataset_deterministic():
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"""Test that dataset generates same items with same seed"""
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config = NumberSortingConfig(seed=42, size=10)
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dataset1 = NumberSortingDataset(config)
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dataset2 = NumberSortingDataset(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_sorting_dataset_items():
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"""Test basic properties of generated items"""
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config = NumberSortingConfig(
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min_numbers=3, max_numbers=6, min_decimals=1, max_decimals=3, min_value=-10.0, max_value=10.0, size=10, seed=42
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)
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dataset = NumberSortingDataset(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 "original_numbers" in item["metadata"]
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assert "direction" in item["metadata"]
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assert "sorted_numbers" in item["metadata"]
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# Verify number count constraints
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numbers = item["metadata"]["original_numbers"]
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print(numbers)
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assert len(numbers) >= config.min_numbers
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assert len(numbers) <= config.max_numbers
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# Verify decimal places
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for num in numbers:
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decimal_places = len(num.split(".")[-1]) if "." in num else 0
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assert decimal_places >= config.min_decimals
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assert decimal_places <= config.max_decimals
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# Verify value range
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for num in numbers:
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value = float(num)
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assert config.min_value <= value <= config.max_value
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# Verify sorting
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direction = item["metadata"]["direction"]
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sorted_numbers = [float(x) for x in eval(item["answer"])]
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if direction == "ascending":
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assert sorted_numbers == sorted(sorted_numbers)
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else:
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assert sorted_numbers == sorted(sorted_numbers, reverse=True)
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def test_number_sorting_dataset_iteration():
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"""Test that iteration respects dataset size"""
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config = NumberSortingConfig(size=5, seed=42)
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dataset = NumberSortingDataset(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_sorting_curriculum():
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curriculum = NumberSortingCurriculum()
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base_value = {"size": 150, "seed": 1}
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base_cfg: NumberSortingConfig = 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_numbers == 10 and base_cfg.max_numbers == 100
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assert base_cfg.min_decimals == 0 and base_cfg.max_decimals == 1
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assert base_cfg.min_value == -100 and base_cfg.max_value == 100
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# test incrementing some attribute levels
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curriculum.increment_attr_level("numbers")
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curriculum.increment_attr_level("decimals")
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increased_cfg = curriculum.generate_configuration(base_value)
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assert increased_cfg.min_numbers == 10 and increased_cfg.max_numbers == 500
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assert increased_cfg.min_decimals == 0 and increased_cfg.max_decimals == 2
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assert increased_cfg.min_value == -100 and increased_cfg.max_value == 100
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# test decrementing attribute level for numbers again
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curriculum.decrement_attr_level("numbers")
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partially_decreased_cfg = curriculum.generate_configuration(base_value)
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assert partially_decreased_cfg.min_numbers == 10 and partially_decreased_cfg.max_numbers == 100
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assert partially_decreased_cfg.min_decimals == 0 and partially_decreased_cfg.max_decimals == 2
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assert partially_decreased_cfg.min_value == -100 and partially_decreased_cfg.max_value == 100
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def test_number_sorting_score_answer():
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"""Test the score_answer method for correctly evaluating model responses."""
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# Create a dataset instance
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config = NumberSortingConfig(seed=42)
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dataset = NumberSortingDataset(config)
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# Create a mock entry similar to the example provided
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mock_entry = {
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"question": "Sort these numbers in ascending order: -16.5, -83.6, -95.7, -97.8, 61.5, 71.08, -92.85",
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"answer": "['-97.8', '-95.7', '-92.8', '-83.6', '-16.5', '61.5', '71.1']",
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"metadata": {
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"direction": "ascending",
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"original_numbers": ["-16.5", "-83.6", "-95.7", "-97.8", "61.5", "71.08", "-92.85"],
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"sorted_numbers": ["-97.8", "-95.7", "-92.8", "-83.6", "-16.5", "61.5", "71.1"],
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},
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}
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# Test case 1: Exact match should score 1.0
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exact_match = "['-97.8', '-95.7', '-92.8', '-83.6', '-16.5', '61.5', '71.1']"
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assert dataset.score_answer(exact_match, mock_entry) == 1.0
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# Test case 2: Answer with small numerical differences but correct order should score 1.0
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close_match = "['-97.8', '-95.7', '-92.85', '-83.6', '-16.5', '61.5', '71.08']"
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assert dataset.score_answer(close_match, mock_entry) == 1.0
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# Test case 3: Incorrectly sorted answer should score 0.0
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wrong_order = "['-16.5', '-83.6', '-92.85', '-95.7', '-97.8', '61.5', '71.08']"
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assert dataset.score_answer(wrong_order, mock_entry) == 0.0
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# Test case 4: Answer with wrong length should score 0.0
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wrong_length = "['-97.8', '-95.7', '-92.85', '-83.6', '-16.5', '61.5']"
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assert dataset.score_answer(wrong_length, mock_entry) == 0.0
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# Test case 5: Non-list answer should score 0.0
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non_list = "'-97.8', '-95.7', '-92.85', '-83.6', '-16.5', '61.5', '71.08'"
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assert dataset.score_answer(non_list, mock_entry) == 0.0
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# Test case 6: None answer should score 0.0
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assert dataset.score_answer(None, mock_entry) == 0.0
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# Test case 7: Correctly sorted but with larger numerical differences (beyond tolerance)
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beyond_tolerance = "['-97.8', '-95.7', '-91.0', '-83.6', '-16.5', '61.5', '72.0']"
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assert dataset.score_answer(beyond_tolerance, mock_entry) == 0.0
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# Test case 8: Descending order test
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descending_entry = {
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"answer": "['71.1', '61.5', '-16.5', '-83.6', '-92.8', '-95.7', '-97.8']",
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"metadata": {
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"direction": "descending",
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"sorted_numbers": ["71.1", "61.5", "-16.5", "-83.6", "-92.8", "-95.7", "-97.8"],
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},
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}
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descending_match = "['71.08', '61.5', '-16.5', '-83.6', '-92.85', '-95.7', '-97.8']"
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assert dataset.score_answer(descending_match, descending_entry) == 1.0
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