"""TinyMind configuration."""
from transformers import PretrainedConfig


class TinyMindConfig(PretrainedConfig):
    model_type = "tiny_smart_llm"

    def __init__(
        self,
        vocab_size: int = 50257,
        n_embd: int = 256,
        n_heads: int = 8,
        n_layers: int = 6,
        max_seq_len: int = 512,
        dropout: float = 0.1,
        **kwargs,
    ):
        self.vocab_size = vocab_size
        self.n_embd = n_embd
        self.n_heads = n_heads
        self.n_layers = n_layers
        self.num_hidden_layers = n_layers  # HF generate() expects this
        self.hidden_size = n_embd          # HF convention
        self.num_attention_heads = n_heads # HF convention
        self.max_seq_len = max_seq_len
        self.max_position_embeddings = max_seq_len  # HF convention
        self.dropout = dropout
        super().__init__(**kwargs)