class_docstr: An implementation of Adam http://arxiv.org/pdf/1412.6980.pdf
  :param learningrate learning rate
  :param learningrate_decay learning rate decay
  :param beta1 first moment coefficient
  :param beta2 second moment coefficient
  :param epsilon for numerical stability
  >>> pAdam = ParallelAdam()
  creating: createParallelAdam
code: def __init__(
      self,
      learningrate=1e-3,
      learningrate_decay=0.0,
      beta1=0.9,
      beta2=0.999,
      epsilon=1e-8,
      parallel_num=-1,
  ):
      from bigdl.optim.optimizer import ParallelAdam as BParallelAdam
  
      self.optimizer = BParallelAdam(
          learningrate,
          learningrate_decay,
          beta1,
          beta2,
          epsilon,
          parallel_num,
          bigdl_type="float",
      )
  
imports: from abc import ABC, abstractmethod
  from bigdl.util.common import DOUBLEMAX
  from zoo.orca.learn.optimizers.schedule import Scheduler
label_desc: Use image node_id 1 to create a new ParallelAdam object from inherited base classes: Optimizer with example: obj = ParallelAdam(learningrate, learningrate_decay, beta1, beta2, epsilon, parallel_num)