code: def update(self, w, grad_wrt_w):
      # If not initialized
      if self.Eg is None:
          self.Eg = np.zeros(np.shape(grad_wrt_w))
  
      self.Eg = self.rho * self.Eg + (1 - self.rho) * np.power(
          grad_wrt_w, 2
      )
  
      # Divide the learning rate for a weight by a running average of the magnitudes of recent
      # gradients for that weight
      return w - self.learning_rate * grad_wrt_w / np.sqrt(
          self.Eg + self.eps
      )
  
file_path: ML-From-Scratch/mlfromscratch/deep_learning/optimizers.py
imports: import numpy
  from mlfromscratch.utils import make_diagonal, normalize
label_desc: Use image node_id 2 for calling the RMSprop obj's underlying member method code with example usage: obj.update(w, grad_wrt_w) and returns: unknown