#Rose X1.5 model configuration.
from transformers import PretrainedConfig


class RoseX15Config(PretrainedConfig):
    
    model_type = "rose_x1_5"

    def __init__(
        self,
        vocab_size=32768,
        hidden_size=576,
        num_hidden_layers=22,
        num_attention_heads=9,
        num_key_value_heads=3,
        head_dim=64,
        intermediate_size=1532,
        max_position_embeddings=4096,
        hidden_act="silu",
        rms_norm_eps=1e-6,
        attention_bias=False,
        mlp_bias=False,
        attention_dropout=0.0,
        rope_theta=100000.0,
        rope_scaling=None,
        tie_word_embeddings=True,
        # QK Norm
        use_qk_norm=True,
        # XSA (Exclusive Self Attention)
        use_xsa=True,
        # Refresh Gate
        refresh_gate_enabled=True,
        refresh_gate_inject_layers=None,
        refresh_gate_kernel_size=9,
        # muP (recorded for reproducibility; does not affect forward pass)
        mup_enabled=False,
        mup_base_hidden_size=None,
        mup_width_mult=None,
        **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.num_key_value_heads = num_key_value_heads
        self.head_dim = head_dim
        self.intermediate_size = intermediate_size
        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.rope_theta = rope_theta
        self.rope_scaling = rope_scaling
        # QK Norm
        self.use_qk_norm = use_qk_norm
        # XSA
        self.use_xsa = use_xsa
        # Refresh Gate
        self.refresh_gate_enabled = refresh_gate_enabled
        self.refresh_gate_inject_layers = (
            list(refresh_gate_inject_layers)
            if refresh_gate_inject_layers is not None
            else [4, 9]
        )
        self.refresh_gate_kernel_size = refresh_gate_kernel_size
        # muP (metadata only)
        self.mup_enabled = mup_enabled
        self.mup_base_hidden_size = mup_base_hidden_size
        self.mup_width_mult = mup_width_mult
        super().__init__(tie_word_embeddings=tie_word_embeddings, **kwargs)