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Merge pull request #12 from Adefioye/koko/scramble
[Level 1 of Unscrambled tasks] - Add sentence reordering and unit tests to validate it
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4 changed files with 134 additions and 0 deletions
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@ -107,6 +107,7 @@ Available dataset names (which can be used with `create_dataset()`):
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- `NumberFilteringDataset`: Filter numbers based on comparison with threshold
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- `NumberSortingDataset`: Sort lists of numbers in ascending or descending order
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- `LetterJumbleDataset`: Unscramble words that have had their letters randomly jumbled
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- `SentenceReorderingDataset`: Reorder sentence after words in it have been randomly shuffled
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- `SpellBackwardDataset`: Spell individual words backward (e.g. "sun" -> "nus")
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- `WordSequenceReversalDataset`: Reverse word order in text spans
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@ -12,6 +12,7 @@ from .letter_counting import LetterCountingConfig, LetterCountingDataset
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from .letter_jumble import LetterJumbleConfig, LetterJumbleDataset
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from .number_filtering import NumberFilteringConfig, NumberFilteringDataset
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from .number_sorting import NumberSortingConfig, NumberSortingDataset
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from .sentence_reordering import SentenceReorderingConfig, SentenceReorderingDataset
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from .spell_backward import SpellBackwardConfig, SpellBackwardDataset
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from .word_sequence_reversal import WordSequenceReversalConfig, WordSequenceReversalDataset
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@ -30,6 +31,8 @@ __all__ = [
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"NumberFilteringDataset",
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"NumberSortingConfig",
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"NumberSortingDataset",
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"SentenceReorderingConfig",
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"SentenceReorderingDataset",
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"WordSequenceReversalConfig",
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"WordSequenceReversalDataset",
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]
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85
reasoning_gym/algorithmic/sentence_reordering.py
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85
reasoning_gym/algorithmic/sentence_reordering.py
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@ -0,0 +1,85 @@
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"""Sentence re-ordering task generator"""
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import re
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from dataclasses import dataclass
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from random import Random
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from typing import List, Optional
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from ..data import read_data_file
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from ..factory import ProceduralDataset, register_dataset
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@dataclass
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class SentenceReorderingConfig:
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"""Configuration for sentence reordering task generation"""
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num_of_words_in_sentence: int = 10
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seed: Optional[int] = None
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size: int = 500
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def validate(self) -> None:
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"""Validate configuration parameters"""
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assert self.num_of_words_in_sentence > 0, "num_of_words_in_sentence must be positive"
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class SentenceReorderingDataset(ProceduralDataset):
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"""Generates sentence reordering tasks from text spans"""
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def __init__(self, config: SentenceReorderingConfig):
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super().__init__(config=config, seed=config.seed, size=config.size)
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# Load and preprocess text
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text = read_data_file("in_the_year_2889.txt")
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# Extract sentences make sure they are greater than or equal to the number of words in a sentence
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# Ensure that only the length of alphanumeric characters in the sentence is considered
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self.sentences = [
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sentence
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for sentence in re.findall(r"[^.!?]+", text)
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if len(re.findall(r"\b\w+\b", sentence)) >= self.config.num_of_words_in_sentence
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]
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def _generate_sentence_dataset(self, sentence: str, seed: int, idx: int, shuffle=True):
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"""
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Generate a procedural dataset by shuffling the words in the input sentence.
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Args:
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sentence (str): The correct sentence to use for dataset generation.
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seed (int): The seed to use for random number generation.
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idx (int): The index to add to the seed for random number generation.
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shuffle (bool): Whether to shuffle the words to create the input sentence.
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Returns:
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dict: A dictionary containing the input sentence and the correct sentence (goal).
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"""
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rng = Random(seed + idx)
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words = sentence.split() # Split the sentence into words
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scrambled_words = words.copy()
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if shuffle:
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rng.shuffle(scrambled_words) # Shuffle the words to generate the input
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input_sentence = " ".join(scrambled_words)
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goal_sentence = " ".join(words)
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return {"input": input_sentence, "goal": goal_sentence}
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def __getitem__(self, idx: int) -> dict:
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"""Generate a single sentence reordering task"""
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rng = Random(self.seed + idx)
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sentence_dataset = self._generate_sentence_dataset(rng.choice(self.sentences), self.seed, idx)
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# Ensure only 'input' and 'goal' keys are present
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if set(sentence_dataset.keys()) != {'input', 'goal'}:
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raise KeyError("The dictionary must contain only 'input' and 'goal' keys")
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# Solve the task by sorting words to match the goal sentence
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input_words = sentence_dataset['input'].split()
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question = " ".join(input_words)
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goal_words = sentence_dataset['goal'].split()
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solved_sentence = " ".join(sorted(input_words, key=lambda word: goal_words.index(word)))
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# Check for length of alphanumeric characters in the solved sentence
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num_of_words_in_sentence = len(re.findall(r"\b\w+\b", solved_sentence))
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return {
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"question": f"Correct the following sentence: {question}",
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"answer": solved_sentence,
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"metadata": {"num_of_words_in_sentence": num_of_words_in_sentence},
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}
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register_dataset("sentence_reordering", SentenceReorderingDataset, SentenceReorderingConfig)
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45
tests/test_sentence_reordering.py
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45
tests/test_sentence_reordering.py
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@ -0,0 +1,45 @@
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import pytest
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from reasoning_gym.algorithmic.sentence_reordering import (
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SentenceReorderingConfig,
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SentenceReorderingDataset,
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)
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@pytest.fixture
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def config():
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return SentenceReorderingConfig(num_of_words_in_sentence=5, seed=42, size=10)
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@pytest.fixture
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def dataset(config):
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return SentenceReorderingDataset(config=config)
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def test_config_validation(config):
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# Test that the config validation does not raise any exceptions
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try:
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config.validate()
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except Exception as e:
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pytest.fail(f"Config validation raised an exception: {e}")
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def test_generate_sentence_dataset(dataset):
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sentence = "This is a test sentence for reordering"
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result = dataset._generate_sentence_dataset(sentence, seed=42, idx=0, shuffle=True)
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assert "input" in result
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assert "goal" in result
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assert result["input"] != result["goal"]
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assert sorted(result["input"].split()) == sorted(result["goal"].split())
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def test_getitem(dataset, config):
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item = dataset[0]
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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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assert item["metadata"]["num_of_words_in_sentence"] >= config.num_of_words_in_sentence
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def test_key_error_in_getitem(dataset):
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# Modify the dataset to include an incorrect key
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def mock_generate_sentence_dataset(*args, **kwargs):
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return {"input": "mock input", "goal": "mock goal", "extra": "extra key"}
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dataset._generate_sentence_dataset = mock_generate_sentence_dataset
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with pytest.raises(KeyError):
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dataset[0]
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