docs: def rmsprop(grad, x, callback=None, num_iters=100,
              step_size=0.1, gamma=0.9, eps=10**-8):
      """Root mean squared prop: See Adagrad paper for details."""
      avg_sq_grad = np.ones(len(x))
      for i in range(num_iters):
          g = grad(x, i)
          if callback: callback(x, i, g)
          avg_sq_grad = avg_sq_grad * gamma + g**2 * (1 - gamma)
          x = x - step_size * g/(np.sqrt(avg_sq_grad) + eps)
      return x