from transformers import PretrainedConfig

QWEN_TOKEN_ID = 151643

AUTO_MAP = {
    "AutoConfig": "configuration_modern_llm.ModernLLMConfig",
    "AutoModelForCausalLM": "modeling_modern_llm.ModernLLMForCausalLM",
}


class ModernLLMConfig(PretrainedConfig):
    model_type = "modern_llm"

    def __init__(
        self,
        vocab_size: int = 151936,
        hidden_size: int = 768,
        intermediate_size: int = 2048,
        num_hidden_layers: int = 12,
        num_attention_heads: int = 12,
        num_key_value_heads: int = 4,
        max_position_embeddings: int = 2048,
        rms_norm_eps: float = 1e-6,
        rope_theta: float = 1000000.0,
        pad_token_id: int = QWEN_TOKEN_ID,
        bos_token_id: int = QWEN_TOKEN_ID,
        eos_token_id: int = QWEN_TOKEN_ID,
        **kwargs,
    ):
        self.vocab_size = vocab_size
        self.hidden_size = hidden_size
        self.intermediate_size = intermediate_size
        self.num_hidden_layers = num_hidden_layers
        self.num_attention_heads = num_attention_heads
        self.num_key_value_heads = num_key_value_heads
        self.max_position_embeddings = max_position_embeddings
        self.rms_norm_eps = rms_norm_eps
        self.rope_theta = rope_theta
        self.auto_map = dict(AUTO_MAP)
        super().__init__(
            pad_token_id=pad_token_id,
            bos_token_id=bos_token_id,
            eos_token_id=eos_token_id,
            **kwargs,
        )