from transformers import PretrainedConfig ,PreTrainedTokenizer

class OBIConfig(PretrainedConfig):
    def __init__(self, 
    model_type="OBILanguageModel", 
    auto_map={
        "AutoConfig": "modelConfig.OBIConfig",
        "AutoModel": "modelLM.OBILanguageModel",
        "AutoModelForCausalLM": "modelLM.OBILanguageModel",
        "AutoModelForQuestionAnswering": "modelLM.OBILanguageModel"
    }, 
    vocab_size=1000, 
    hidden_size=4, 
    num_attention_heads=2, 
    num_hidden_layers=2, 
    hidden_dropout_prob=0.1, 
    block_size=100, 
    batch_size=60,
    max_iters=200,
    eval_interval=100,
    learning_rate=0.001,
    device="cpu",
    **kwargs
    )->None:
        super().__init__(**kwargs)
        self.model_type = model_type
        self.auto_map = auto_map
        self.vocab_size = vocab_size
        self.hidden_size = hidden_size
        self.num_attention_heads = num_attention_heads
        self.num_hidden_layers = num_hidden_layers
        self.hidden_dropout_prob = hidden_dropout_prob
        self.block_size = block_size
        self.batch_size = batch_size
        self.max_iters = max_iters
        self.eval_interval = eval_interval
        self.learning_rate = learning_rate
        self.device = device