from transformers import PretrainedConfig


class HareConfig(PretrainedConfig):
    model_type = "hare"

    def __init__(
        self,
        hidden_size=768,
        num_attention_heads=12,
        num_hidden_layers=22,
        intermediate_size=1152,
        hidden_activation="gelu",
        max_position_embeddings=8192,
        vocab_size=50368,
        pad_token_id=50283,
        bos_token_id=50281,
        eos_token_id=50282,
        cls_token_id=50281,
        sep_token_id=50282,
        global_attn_every_n_layers=3,
        local_attention=128,
        replaced_layers=None,
        surgery_variant="conservative",
        **kwargs,
    ):
        super().__init__(
            pad_token_id=pad_token_id,
            bos_token_id=bos_token_id,
            eos_token_id=eos_token_id,
            **kwargs,
        )
        self.hidden_size = hidden_size
        self.num_attention_heads = num_attention_heads
        self.num_hidden_layers = num_hidden_layers
        self.intermediate_size = intermediate_size
        self.hidden_activation = hidden_activation
        self.max_position_embeddings = max_position_embeddings
        self.vocab_size = vocab_size
        self.cls_token_id = cls_token_id
        self.sep_token_id = sep_token_id
        self.global_attn_every_n_layers = global_attn_every_n_layers
        self.local_attention = local_attention
        self.replaced_layers = replaced_layers
        self.surgery_variant = surgery_variant