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added curriculum
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19 changed files with 1104 additions and 450 deletions
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@ -17,7 +17,7 @@ class SpellBackwardConfig:
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"""Configuration for spelling words backward task generation"""
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min_word_len: int = 3 # Minimum word length
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max_word_len: int = 20 # Maximum word length
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max_word_len: int = 10 # Maximum word length
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seed: Optional[int] = None
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size: int = 500 # Virtual dataset size
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@ -34,12 +34,11 @@ class SpellBackwardDataset(ProceduralDataset):
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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 words and clean them to contain only alphanumeric characters
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text = read_data_file("words3to10.txt")
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self.words = [
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word
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for word in re.findall(r"\b\w+\b", text)
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if word.isalnum() and config.min_word_len <= len(word) <= config.max_word_len
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word.strip()
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for word in text.splitlines()
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if word.strip().isalnum() and config.min_word_len <= len(word.strip()) <= config.max_word_len
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]
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def __getitem__(self, idx: int) -> dict:
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@ -71,6 +70,8 @@ class SpellBackwardDataset(ProceduralDataset):
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try:
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if expected_answer.lower() == answer.lower():
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reward = 1.0
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elif sorted(expected_answer.lower()) == sorted(answer.lower()):
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reward = 0.2
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else:
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reward = 0.05
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except:
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@ -86,11 +87,11 @@ class SpellBackwardCurriculum(BaseCurriculum):
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self._define_attributes(
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RangeAttributeDefinition(
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name="word_len",
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levels=[5, 10, 20, 30],
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levels=list(range(3, 11)),
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description="Word length",
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lower_field_name="min_word_len",
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upper_field_name="max_word_len",
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ensure_interval=True,
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ensure_interval=False,
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),
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)
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