from transformers import PretrainedConfig, AutoConfig

class BERTMultiGATAttentionConfig(PretrainedConfig):
    model_type = "deberta_semantic_similarity"


    def __init__(
        self,
        transformer_model='microsoft/deberta-v3-base',
        hidden_size=768,
        num_heads=8,
        dropout=0.07,
        gnn_input_dim=768,
        gnn_hidden_dim=768,
        **kwargs
    ):
        super().__init__(**kwargs)
        self.transformer_model = transformer_model
        self.hidden_size = hidden_size
        self.num_heads = num_heads
        self.dropout = dropout
        self.gnn_input_dim = gnn_input_dim
        self.gnn_hidden_dim = gnn_hidden_dim


AutoConfig.register("deberta_semantic_similarity", BERTMultiGATAttentionConfig)