from transformers import PretrainedConfig


class BinaryLLMConfig(PretrainedConfig):
    model_type = "binaryllm"

    def __init__(
        self,
        vocab_size: int = 65538,
        hidden_size: int = 512,
        num_hidden_layers: int = 4,
        num_attention_heads: int = 4,
        intermediate_size: int = 2048,
        max_position_embeddings: int = 2048,
        dropout: float = 0.1,
        activation: str = "gelu",
        bos_token_id: int = 65536,
        eos_token_id: int = 65537,
        pad_token_id: int = 65537,
        **kwargs,
    ):
        self.vocab_size = int(vocab_size)
        self.hidden_size = int(hidden_size)
        self.num_hidden_layers = int(num_hidden_layers)
        self.num_attention_heads = int(num_attention_heads)
        self.intermediate_size = int(intermediate_size)
        self.max_position_embeddings = int(max_position_embeddings)
        self.dropout = float(dropout)
        self.activation = str(activation)

        self.bos_token_id = int(bos_token_id)
        self.eos_token_id = int(eos_token_id)
        self.pad_token_id = int(pad_token_id)

        super().__init__(**kwargs)