"""Hugging Face PretrainedConfig wrapper for SimpleLM (auto-generated)."""

from __future__ import annotations

from typing import Optional

from transformers import PretrainedConfig


class SimpleLMConfig(PretrainedConfig):
    model_type = "simple_lm"

    def __init__(
        self,
        vocab_size: int = 32000,
        context_length: int = 512,
        d_model: int = 512,
        n_layers: int = 8,
        n_heads: int = 8,
        d_ff: Optional[int] = None,
        dropout: float = 0.1,
        activation: str = "gelu",
        bias: bool = True,
        tie_word_embeddings: bool = True,
        **kwargs,
    ) -> None:
        super().__init__(tie_word_embeddings=tie_word_embeddings, **kwargs)
        self.vocab_size = vocab_size
        self.context_length = context_length
        self.d_model = d_model
        self.n_layers = n_layers
        self.n_heads = n_heads
        self.d_ff = d_ff
        self.dropout = dropout
        self.activation = activation
        self.bias = bias

    @property
    def hidden_size(self) -> int:
        return self.d_model

    @property
    def max_position_embeddings(self) -> int:
        return self.context_length

    @property
    def num_hidden_layers(self) -> int:
        return self.n_layers

    @property
    def num_attention_heads(self) -> int:
        return self.n_heads