from __future__ import annotations

from typing import Optional

from transformers import PretrainedConfig

from babylm.config.schema import ModelConfig


class ModernBertSmallConfig(PretrainedConfig):
    """HF-compatible config for the from-scratch ModernBERT-Small architecture.

    Bridges to the pydantic `ModelConfig` (used for JSON validation/CLI) via `to_hf_config`,
    while giving `save_pretrained`/`from_pretrained`/`AutoConfig` compatibility.
    """

    model_type = "modernbert_small"

    def __init__(
        self,
        vocab_size: int = 30522,
        hidden_size: int = 384,
        num_hidden_layers: int = 16,
        num_attention_heads: int = 6,
        intermediate_size: int = 576,
        hidden_activation: str = "gelu",
        attention_pattern: str = "alternating",
        global_attn_every_n_layers: int = 3,
        global_rope_theta: float = 160000.0,
        local_rope_theta: float = 10000.0,
        local_attention_window: int = 128,
        norm_eps: float = 1e-5,
        attention_dropout: float = 0.0,
        mlp_dropout: float = 0.0,
        embedding_dropout: float = 0.0,
        embedding_type: str = "standard",
        factorized_linear_bottleneck_dim: int = 128,
        factorized_mlp_bottleneck_dim: int = 128,
        initializer_range: float = 0.02,
        pad_token_id: int = 0,
        tie_word_embeddings: bool = True,
        **kwargs,
    ) -> None:
        super().__init__(pad_token_id=pad_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.hidden_activation = hidden_activation
        self.attention_pattern = attention_pattern
        self.global_attn_every_n_layers = global_attn_every_n_layers
        self.global_rope_theta = global_rope_theta
        self.local_rope_theta = local_rope_theta
        self.local_attention_window = local_attention_window
        self.norm_eps = norm_eps
        self.attention_dropout = attention_dropout
        self.mlp_dropout = mlp_dropout
        self.embedding_dropout = embedding_dropout
        self.embedding_type = embedding_type
        self.factorized_linear_bottleneck_dim = factorized_linear_bottleneck_dim
        self.factorized_mlp_bottleneck_dim = factorized_mlp_bottleneck_dim
        self.initializer_range = initializer_range


def to_hf_config(model_cfg: ModelConfig, pad_token_id: Optional[int] = None) -> ModernBertSmallConfig:
    """Builds a ModernBertSmallConfig from the pydantic ModelConfig, optionally overriding
    pad_token_id with the value discovered from a trained tokenizer."""
    data = model_cfg.model_dump()
    if pad_token_id is not None:
        data["pad_token_id"] = pad_token_id
    return ModernBertSmallConfig(**data)