class_docstr: Stochastic gradient descent optimizer.
  
  V = bV + aG
  W = W - V
  
  Reference: https://paperswithcode.com/method/sgd-with-momentum
code: def __init__(self, learning_rate=0.01, momentum=0.0):
      self.learning_rate = learning_rate
      self.momentum = momentum
      self.Vs = {}
  
file_path: tf-encrypted/tf_encrypted/keras/optimizers.py
imports: import numpy
  import tensorflow
  import tf_encrypted
label_desc: Use image node_id 1 to create a new SGD object  with example: obj = SGD(learning_rate, momentum)