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93 lines
3 KiB
Python
93 lines
3 KiB
Python
"""Letter counting task generator"""
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from dataclasses import dataclass
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import re
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from random import Random
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from typing import List, Optional
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from reasoning_gym.data import read_data_file
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@dataclass
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class LetterCountingConfig:
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"""Configuration for letter counting task generation"""
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min_words: int = 5 # Minimum words in span
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max_words: int = 15 # Maximum words in span
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seed: Optional[int] = None
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size: int = 500 # Virtual dataset size
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def validate(self):
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"""Validate configuration parameters"""
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assert self.min_words > 0, "min_words must be positive"
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assert self.max_words >= self.min_words, "max_words must be >= min_words"
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class LetterCountingDataset:
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"""Generates letter counting tasks from text spans"""
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def __init__(self, config: LetterCountingConfig):
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self.config = config
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self.config.validate()
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self.seed = config.seed if config.seed is not None else Random().randint(0, 2**32)
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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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self.words = [word for word in re.findall(r'\b\w+\b', text)]
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def __len__(self) -> int:
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return self.config.size
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def __iter__(self):
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self._current_idx = 0
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return self
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def __next__(self):
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if self._current_idx >= self.config.size:
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raise StopIteration
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item = self[self._current_idx]
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self._current_idx += 1
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return item
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def __getitem__(self, idx: int) -> dict:
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"""Generate a single letter counting task"""
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rng = Random(self.seed + idx)
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# Select random span of words
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span_length = rng.randint(self.config.min_words, self.config.max_words)
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start_idx = rng.randint(0, len(self.words) - span_length)
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span = self.words[start_idx:start_idx + span_length]
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# Get all unique letters from span
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letters = set(''.join(span).lower())
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if not letters:
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letters = {'a'} # Fallback if span has no letters
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# Select random letter that appears in the span
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target_letter = rng.choice(list(letters))
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# Count occurrences
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count = sum(word.lower().count(target_letter) for word in span)
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return {
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"question": f'How many times does the letter "{target_letter}" appear in the text: "{" ".join(span)}"?',
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"answer": str(count),
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"metadata": {
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"span_length": span_length,
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"target_letter": target_letter,
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"span": span
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}
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}
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def letter_counting_dataset(
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min_words: int = 5,
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max_words: int = 15,
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seed: Optional[int] = None,
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size: int = 500,
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) -> LetterCountingDataset:
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"""Create a LetterCountingDataset with the given configuration."""
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config = LetterCountingConfig(
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min_words=min_words,
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max_words=max_words,
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seed=seed,
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size=size,
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)
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return LetterCountingDataset(config)
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