class_docstr: Simple Momentum optimizer with velocity state.
  Args:
      learning_rate (float|Variable) - The learning rate used to update parameters.
          Can be a float value or a Variable with one float value as data element.
      momentum (float) - Momentum factor.
      regularization (WeightDecayRegularizer, optional) - The strategy of regularization.
class_docstr_tok: ["Simple","Momentum","optimizer","with","velocity","state",".","Args",":","learning_rate","(","float|Variable",")","-","The","learning","rate","used","to","update","parameters",".","Can","be","a","float","value","or","a","Variable","with","one","float","value","as","data","element",".","momentum","(","float",")","-","Momentum","factor",".","regularization","(","WeightDecayRegularizer",",","optional",")","-","The","strategy","of","regularization","."]
code: def __init__(
      self,
      learning_rate,
      momentum,
      weight_decay=None,
      grad_clip=None,
      **args,
  ):
      super(Momentum, self).__init__()
      self.learning_rate = learning_rate
      self.momentum = momentum
      self.weight_decay = weight_decay
      self.grad_clip = grad_clip
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  from paddle import optimizer
label_desc: Use image node_id 1 to create a new Momentum object from inherited base classes: object with example: obj = Momentum(learning_rate, momentum, weight_decay, grad_clip)