pass config to ProceduralDataset base

reasoning_gym/algorithmic/base_conversion.py

@@ -18,7 +18,7 @@ class BaseConversionConfig:
     seed: Optional[int] = None
     size: int = 500  # Virtual dataset size
 
-    def validate(self):
+    def validate(self) -> None:
         """Validate configuration parameters"""
         assert 2 <= self.min_base <= 36, "min_base must be between 2 and 36"
         assert self.min_base <= self.max_base <= 36, "max_base must be between min_base and 36"
@@ -30,9 +30,7 @@ class BaseConversionDataset(ProceduralDataset):
     """Generates base conversion tasks"""
 
     def __init__(self, config: BaseConversionConfig):
-        self.config = config
-        self.config.validate()
-        super().__init__(seed=config.seed, size=config.size)
+        super().__init__(config=config, seed=config.seed, size=config.size)
 
     def _format_base_name(self, base: int) -> str:
         """Get human-readable name for common bases"""

reasoning_gym/algorithmic/letter_counting.py

@@ -19,7 +19,7 @@ class LetterCountingConfig:
     seed: Optional[int] = None
     size: int = 500  # Virtual dataset size
 
-    def validate(self):
+    def validate(self) -> None:
         """Validate configuration parameters"""
         assert self.min_words > 0, "min_words must be positive"
         assert self.max_words >= self.min_words, "max_words must be >= min_words"
@@ -29,9 +29,7 @@ class LetterCountingDataset(ProceduralDataset):
     """Generates letter counting tasks from text spans"""
 
     def __init__(self, config: LetterCountingConfig):
-        self.config = config
-        self.config.validate()
-        super().__init__(seed=config.seed, size=config.size)
+        super().__init__(config=config, seed=config.seed, size=config.size)
 
         # Load and preprocess text
         text = read_data_file("in_the_year_2889.txt")

reasoning_gym/algorithmic/number_filtering.py

@@ -20,7 +20,7 @@ class NumberFilteringConfig:
     seed: Optional[int] = None
     size: int = 500  # Virtual dataset size
 
-    def validate(self):
+    def validate(self) -> None:
         """Validate configuration parameters"""
         assert self.min_numbers > 0, "min_numbers must be positive"
         assert self.max_numbers >= self.min_numbers, "max_numbers must be >= min_numbers"
@@ -33,9 +33,7 @@ class NumberFilteringDataset(ProceduralDataset):
     """Generates number filtering tasks"""
 
     def __init__(self, config: NumberFilteringConfig):
-        self.config = config
-        self.config.validate()
-        super().__init__(seed=config.seed, size=config.size)
+        super().__init__(config=config, seed=config.seed, size=config.size)
 
     def _format_number(self, num: float, decimals: int) -> str:
         """Format a number with specified decimal places"""

reasoning_gym/algorithmic/number_sorting.py

@@ -20,7 +20,7 @@ class NumberSortingConfig:
     seed: Optional[int] = None
     size: int = 500  # Virtual dataset size
 
-    def validate(self):
+    def validate(self) -> None:
         """Validate configuration parameters"""
         assert self.min_numbers > 0, "min_numbers must be positive"
         assert self.min_numbers <= self.max_numbers, "max_numbers must be >= min_numbers"
@@ -33,9 +33,7 @@ class NumberSortingDataset(ProceduralDataset):
     """Generates number sorting tasks"""
 
     def __init__(self, config: NumberSortingConfig):
-        self.config = config
-        self.config.validate()
-        super().__init__(seed=config.seed, size=config.size)
+        super().__init__(config=config, seed=config.seed, size=config.size)
 
     def _format_number(self, num: float, decimals: int) -> str:
         """Format number with specified decimal places"""

reasoning_gym/algorithmic/word_reversal.py

@@ -18,7 +18,7 @@ class WordReversalConfig:
     seed: Optional[int] = None
     size: int = 500  # Virtual dataset size
 
-    def validate(self):
+    def validate(self) -> None:
         """Validate configuration parameters"""
         assert self.min_words > 0, "min_words must be positive"
         assert self.max_words >= self.min_words, "max_words must be >= min_words"
@@ -28,9 +28,7 @@ class WordReversalDataset(ProceduralDataset):
     """Generates word reversal tasks from text spans"""
 
     def __init__(self, config: WordReversalConfig):
-        self.config = config
-        self.config.validate()
-        super().__init__(seed=config.seed, size=config.size)
+        super().__init__(config=config, seed=config.seed, size=config.size)
 
         # Load and preprocess text
         text = read_data_file("in_the_year_2889.txt")