code: def rmsprop(step_size, gamma=0.9, eps=1e-8):
      """Construct optimizer triple for RMSProp.
  
      Args:
        step_size: positive scalar, or a callable representing a step size schedule
          that maps the iteration index to a positive scalar.
          gamma: Decay parameter.
          eps: Epsilon parameter.
  
      Returns:
        An (init_fun, update_fun, get_params) triple.
      """
      step_size = make_schedule(step_size)
  
      def init(x0):
          avg_sq_grad = jnp.zeros_like(x0)
          return x0, avg_sq_grad
  
      def update(i, g, state):
          x, avg_sq_grad = state
          avg_sq_grad = avg_sq_grad * gamma + jnp.square(g) * (
              1.0 - gamma
          )
          x = x - step_size(i) * g / jnp.sqrt(avg_sq_grad + eps)
          return x, avg_sq_grad
  
      def get_params(state):
          x, _ = state
          return x
  
      return init, update, get_params
  
imports: from __future__ import annotations
  from typing import Any, Callable, NamedTuple
  from collections import namedtuple
  import functools
  from functools import partial
  import jax.numpy
  from jax._src.util import safe_zip, safe_map, unzip2
  from jax import tree_util
  from jax.tree_util import tree_map, tree_flatten, tree_unflatten, register_pytree_node
label_desc: Use image node_id 6 for calling a global function with example usage: rmsprop(step_size, gamma, eps) and returns: init,  update,  get_params, x0,  avg_sq_grad, x,  avg_sq_grad, x