def METHOD_NAME(self, grad, var, apply_state=None):
    var_device, var_dtype = var.device, var.dtype.base_dtype
    coefficients = (apply_state or {}).get(
        (var_device, var_dtype)
    ) or self._fallback_apply_state(var_device, var_dtype)
    acc = self.get_slot(var, "accumulator")
    return tf.raw_ops.ResourceApplyProximalAdagrad(
        var=var.handle,
        accum=acc.handle,
        lr=coefficients["lr_t"],
        l1=coefficients["l1_regularization_strength"],
        l2=coefficients["l2_regularization_strength"],
        grad=grad,
        use_locking=self._use_locking,
    )