"""HuggingFace configuration for the Rose X1 architecture."""
from transformers import PretrainedConfig


class RoseX1Config(PretrainedConfig):
    model_type = "rose_x1"

    def __init__(
        self,
        vocab_size=16384,
        hidden_size=512,
        intermediate_size=1408,
        num_hidden_layers=14,
        num_attention_heads=8,
        num_key_value_heads=2,
        head_dim=None,
        max_position_embeddings=1024,
        hidden_act="silu",
        rms_norm_eps=1e-5,
        attention_bias=False,
        mlp_bias=False,
        attention_dropout=0.0,
        tie_word_embeddings=True,
        rope_theta=100000.0,
        rope_scaling=None,
        initializer_range=0.02,
        use_cache=True,
        # ── Rose X1 specifics ──────────────────────────────────────────────
        use_qk_norm=True,
        refresh_gate_enabled=True,
        refresh_gate_inject_layers=None,
        refresh_gate_kernel_size=9,
        **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.head_dim = head_dim if head_dim is not None else hidden_size // num_attention_heads
        self.max_position_embeddings = max_position_embeddings
        self.hidden_act = hidden_act
        self.rms_norm_eps = rms_norm_eps
        self.attention_bias = attention_bias
        self.mlp_bias = mlp_bias
        self.attention_dropout = attention_dropout
        self.tie_word_embeddings = tie_word_embeddings
        self.rope_theta = rope_theta
        self.rope_scaling = rope_scaling
        self.initializer_range = initializer_range
        self.use_cache = use_cache
        self.use_qk_norm = use_qk_norm
        self.refresh_gate_enabled = refresh_gate_enabled
        self.refresh_gate_inject_layers = (
            list(refresh_gate_inject_layers) if refresh_gate_inject_layers else []
        )
        self.refresh_gate_kernel_size = refresh_gate_kernel_size
        super().__init__(**kwargs)