src/transformers/models/longformer/configuration_longformer.py/LongformerConfig/__init__
class LongformerConfig:    def __init__(
        self,
        attention_window: Union[List[int], int] = 512,
        sep_token_id: int = 2,
        pad_token_id: int = 1,
        bos_token_id: int = 0,
        eos_token_id: int = 2,
        vocab_size: int = 30522,
        hidden_size: int = 768,
        num_hidden_layers: int = 12,
        num_attention_heads: int = 12,
        intermediate_size: int = 3072,
        hidden_act: str = "gelu",
        hidden_dropout_prob: float = 0.1,
        attention_probs_dropout_prob: float = 0.1,
        max_position_embeddings: int = 512,
        type_vocab_size: int = 2,
        initializer_range: float = 0.02,
        layer_norm_eps: float = 1e-12,
        position_embedding_type: str = "absolute",
        onnx_export: bool = False,
        **kwargs,
    ):
        """Constructs LongformerConfig."""
        super().__init__(pad_token_id=pad_token_id, **kwargs)

        self.attention_window = attention_window
        self.sep_token_id = sep_token_id
        self.bos_token_id = bos_token_id
        self.eos_token_id = eos_token_id
        self.vocab_size = vocab_size
        self.hidden_size = hidden_size
        self.num_hidden_layers = num_hidden_layers
        self.num_attention_heads = num_attention_heads
        self.hidden_act = hidden_act
        self.intermediate_size = intermediate_size
        self.hidden_dropout_prob = hidden_dropout_prob
        self.attention_probs_dropout_prob = attention_probs_dropout_prob
        self.max_position_embeddings = max_position_embeddings
        self.type_vocab_size = type_vocab_size
        self.initializer_range = initializer_range
        self.layer_norm_eps = layer_norm_eps
        self.position_embedding_type = position_embedding_type
        self.onnx_export = onnx_export