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https://github.com/open-thought/reasoning-gym.git
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135 lines
4.3 KiB
Python
135 lines
4.3 KiB
Python
from random import Random
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import pytest
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from reasoning_gym.games.emoji_mystery import EmojiMysteryConfig, EmojiMysteryCurriculum, EmojiMysteryDataset
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def test_emoji_mystery_config_validation():
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"""Test that config validation works"""
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config = EmojiMysteryConfig(size=-1)
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with pytest.raises(AssertionError):
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config.validate()
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def test_emoji_mystery_deterministic():
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"""Test that dataset generates same items with same seed"""
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config = EmojiMysteryConfig(seed=42, size=10)
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dataset1 = EmojiMysteryDataset(config)
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dataset2 = EmojiMysteryDataset(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_emoji_mystery_items():
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"""Test basic properties of generated items"""
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config = EmojiMysteryConfig(size=100, seed=42)
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dataset = EmojiMysteryDataset(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 isinstance(item["question"], str)
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assert isinstance(item["answer"], str)
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def test_emoji_mystery_iteration():
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"""Test that iteration respects dataset size"""
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config = EmojiMysteryConfig(size=5, seed=42) # Small size for testing
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dataset = EmojiMysteryDataset(config)
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# Test manual iteration
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items = []
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for item in dataset:
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items.append(item)
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assert len(items) == config.size, "Iterator should yield exactly size items"
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# Test list conversion
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items = list(dataset)
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assert len(items) == config.size, "Iterator should yield exactly size items"
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# Test multiple iterations
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first_items = list(dataset)
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second_items = list(dataset)
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assert first_items == second_items, "Multiple iterations should yield same items"
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def test_emoji_mystery_encoding_decoding():
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"""Test the encoding and decoding functionality"""
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config = EmojiMysteryConfig()
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dataset = EmojiMysteryDataset(config)
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# Test with a simple sentence
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test_sentence = "Hello, World!"
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test_emoji = "😀"
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# Test encoding
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encoded = dataset.encode(test_sentence, test_emoji)
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assert encoded.startswith(test_emoji)
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# Test decoding
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decoded = dataset.decode(encoded)
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assert decoded == test_sentence
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# Test with various sentences
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test_cases = [
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"A simple test.",
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"More complex sentence with numbers 123!",
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"Special characters: @#$%^&*()",
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]
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for sentence in test_cases:
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encoded = dataset.encode(sentence, test_emoji)
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decoded = dataset.decode(encoded)
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assert decoded == sentence
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def test_emoji_mystery_scoring():
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"""Test the scoring functionality"""
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config = EmojiMysteryConfig()
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dataset = EmojiMysteryDataset(config)
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# Test exact match
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entry = {"answer": "Test answer"}
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assert dataset.score_answer("Test answer", entry) == 1.0
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# Test partial match
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assert dataset.score_answer("Test answe", entry) == 0.01 # Different length
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# Test None answer
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assert dataset.score_answer(None, entry) == 0.0
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def test_emoji_mystery_curriculum():
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"""Test the emoji mystery curriculum functionality"""
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curriculum = EmojiMysteryCurriculum()
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base_value = {"size": 150, "seed": 1}
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# Test base configuration
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base_cfg: EmojiMysteryConfig = 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_words_in_sentence == 3
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assert base_cfg.max_words_in_sentence == 3
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# Test incrementing attribute level
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curriculum.increment_attr_level("num_words_in_sentence")
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increased_cfg = curriculum.generate_configuration(base_value)
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assert increased_cfg.min_words_in_sentence == 10
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assert increased_cfg.max_words_in_sentence == 10
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# Test incrementing attribute level again
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curriculum.increment_attr_level("num_words_in_sentence")
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double_increased_cfg = curriculum.generate_configuration(base_value)
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assert double_increased_cfg.min_words_in_sentence == 20
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assert double_increased_cfg.max_words_in_sentence == 20
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# Test decrementing attribute level
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curriculum.decrement_attr_level("num_words_in_sentence")
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decreased_cfg = curriculum.generate_configuration(base_value)
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assert decreased_cfg.min_words_in_sentence == 10
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assert decreased_cfg.max_words_in_sentence == 10
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