class_docstr: A learning rate decay policy, where the effective learning rate
  follows a polynomial decay, to be zero by the max_epochs.
  Calculation: init_lr * (1 - epoch/max_iteration) ^ (power)
  
  
  :param power: The coefficient of decay.
  :param max_epochs: The maximum number of epochs when lr becomes zero.
  
  >>> poly = PolyEpochDecay(0.5, 5)
  creating: createZooKerasPolyEpochDecay
class_docstr_tok: ["A","learning","rate","decay","policy",",","where","the","effective","learning","rate","follows","a","polynomial","decay",",","to","be","zero","by","the","max_epochs",".","Calculation",":","init_lr","*","(","1","-","epoch\/max_iteration",")","^","(","power",")",":","param","power",":","The","coefficient","of","decay",".",":","param","max_epochs",":","The","maximum","number","of","epochs","when","lr","becomes","zero",".",">",">",">","poly","=","PolyEpochDecay","(","0.5",",","5",")","creating",":","createZooKerasPolyEpochDecay"]
code: def __init__(self, power, max_epochs, bigdl_type="float"):
      JavaValue.__init__(self, None, bigdl_type, power, max_epochs)
  
file_path: BigDL/python/dllib/src/bigdl/dllib/keras/optimizers.py
imports: from bigdl.dllib.utils.common import *
  from bigdl.dllib.optim.optimizer import OptimMethod, Default
  from bigdl.dllib.keras.base import ZooKerasCreator
  from bigdl.dllib.utils.file_utils import callZooFunc
label_desc: Use image node_id 1 to create a new PolyEpochDecay object from inherited base classes: ZooKerasCreator with example: obj = PolyEpochDecay(power, max_epochs, bigdl_type)