class_docstr: Simple Momentum optimizer with velocity state.
  
  Args:
      args(Namespace): Arguments obtained from ArgumentParser.
      learning_rate(float|LRScheduler): The learning rate used to update parameters.
          Can be a float value or a paddle.optimizer.lr.LRScheduler.
code: def __call__(self):
      # model_list is None in static graph
      parameters = None
      opt = optim.Momentum(
          learning_rate=self.learning_rate,
          momentum=self.momentum,
          weight_decay=self.weight_decay,
          grad_clip=self.grad_clip,
          multi_precision=self.multi_precision,
          parameters=parameters,
      )
      return opt
  
imports: import sys
  import logging
  from paddle import optimizer
label_desc: Use image node_id 2 for calling the Momentum obj's underlying member method code with example usage: obj.__call__() and returns: opt