def METHOD_NAME(self):
    config = super().METHOD_NAME()
    activation = self.activation
    if not isinstance(activation, (str, dict)):
        activation = keras.activations.serialize(activation)
    config.update(
        {
            "project_dim": self.project_dim,
            "mlp_dim": self.mlp_dim,
            "num_heads": self.num_heads,
            "attention_dropout": self.attention_dropout,
            "mlp_dropout": self.mlp_dropout,
            "activation": activation,
            "layer_norm_epsilon": self.layer_norm_epsilon,
        }
    )
    return config