Create configuration_mixture_of_recursions.py

configuration_mixture_of_recursions.py

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+# configuration_mixture_of_recursions.py
+# Create this file in your repository root
+
+from transformers import PretrainedConfig
+
+
+class MixtureOfRecursionsConfig(PretrainedConfig):
+    """
+    Configuration class for MixtureOfRecursions model.
+    
+    This class stores the configuration of a MixtureOfRecursions model with recursive transformers.
+    """
+    model_type = "mixture_of_recursions"
+    
+    def __init__(
+        self,
+        vocab_size=10000,
+        hidden_size=256,
+        num_hidden_layers=4,
+        num_attention_heads=8,
+        intermediate_size=1024,
+        max_position_embeddings=512,
+        max_recursion_depth=3,
+        attention_dropout=0.1,
+        hidden_dropout=0.1,
+        initializer_range=0.02,
+        layer_norm_eps=1e-5,
+        use_cache=True,
+        pad_token_id=0,
+        bos_token_id=1,
+        eos_token_id=2,
+        tie_word_embeddings=False,
+        **kwargs
+    ):
+        """
+        Args:
+            vocab_size (int): Vocabulary size of the model
+            hidden_size (int): Dimension of the hidden representations
+            num_hidden_layers (int): Number of transformer layers
+            num_attention_heads (int): Number of attention heads
+            intermediate_size (int): Dimension of the feedforward network
+            max_position_embeddings (int): Maximum sequence length
+            max_recursion_depth (int): Maximum depth of recursive processing
+            attention_dropout (float): Dropout probability for attention layers
+            hidden_dropout (float): Dropout probability for hidden layers
+            initializer_range (float): Standard deviation for weight initialization
+            layer_norm_eps (float): Epsilon for layer normalization
+            use_cache (bool): Whether to use past key values for faster generation
+            pad_token_id (int): Token ID for padding
+            bos_token_id (int): Token ID for beginning of sequence
+            eos_token_id (int): Token ID for end of sequence
+            tie_word_embeddings (bool): Whether to tie input and output embeddings
+        """
+        super().__init__(
+            pad_token_id=pad_token_id,
+            bos_token_id=bos_token_id,
+            eos_token_id=eos_token_id,
+            tie_word_embeddings=tie_word_embeddings,
+            **kwargs
+        )
+        
+        self.vocab_size = vocab_size
+        self.hidden_size = hidden_size
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads
+        self.intermediate_size = intermediate_size
+        self.max_position_embeddings = max_position_embeddings
+        self.max_recursion_depth = max_recursion_depth
+        self.attention_dropout = attention_dropout
+        self.hidden_dropout = hidden_dropout
+        self.initializer_range = initializer_range
+        self.layer_norm_eps = layer_norm_eps
+        self.use_cache = use_cache