from transformers import PretrainedConfig


class SpecT1Config(PretrainedConfig):
    model_type = "spect1"

    def __init__(
        self,
        hidden_size=4096,
        intermediate_size=11008,
        num_attention_heads=32,
        num_hidden_layers=36,
        max_position_embeddings=32768,
        vocab_size=151680,
        attention_dropout=0.0,
        hidden_act="silu",
        max_window_layers=36,
        rope_theta=640000,
        sliding_window=32768,
        attention_bias=True,
        num_nextn_predict_layers=1,
        initializer_range=0.02,
        bos_token_id=151643,
        eos_token_id=151645,
        tie_word_embeddings=False,
        **kwargs
    ):
        super().__init__(**kwargs)
        self.hidden_size = hidden_size
        self.intermediate_size = intermediate_size
        self.num_attention_heads = num_attention_heads
        self.num_hidden_layers = num_hidden_layers
        self.max_position_embeddings = max_position_embeddings
        self.vocab_size = vocab_size
        self.attention_dropout = attention_dropout
        self.hidden_act = hidden_act
        self.max_window_layers = max_window_layers
        self.rope_theta = rope_theta
        self.sliding_window = sliding_window
        self.attention_bias = attention_bias
        self.num_nextn_predict_layers = num_nextn_predict_layers
        self.initializer_range = initializer_range
        self.bos_token_id = bos_token_id
        self.eos_token_id = eos_token_id
        self.tie_word_embeddings = tie_word_embeddings