src/transformers/models/deberta/modeling_tf_deberta.py/TFDebertaEncoder/__init__
class TFDebertaEncoder:    def __init__(self, config: DebertaConfig, **kwargs):
        super().__init__(**kwargs)

        self.layer = [TFDebertaLayer(config, name=f"layer_._{i}") for i in range(config.num_hidden_layers)]
        self.relative_attention = getattr(config, "relative_attention", False)
        self.config = config
        if self.relative_attention:
            self.max_relative_positions = getattr(config, "max_relative_positions", -1)
            if self.max_relative_positions < 1:
                self.max_relative_positions = config.max_position_embeddings