keras/src/optimizers/nadam.py/Nadam/_backend_update_step
class Nadam:    def _backend_update_step(self, grads, trainable_variables, learning_rate):
        dtype = self._u_product.dtype
        self.assign(
            self._u_product,
            self._u_product
            * self.beta_1
            * (
                1.0
                - 0.5 * ops.power(0.96, ops.cast(self.iterations + 1, dtype))
            ),
        )
        super()._backend_update_step(grads, trainable_variables, learning_rate)