class_docstr: It caculates diff = K.abs((y - x) / K.clip(K.abs(y), K.epsilon(), Double.MaxValue))
  and return 100 * K.mean(diff) as outpout
  
  >>> loss = MeanAbsolutePercentageError()
  creating: createZooKerasMeanAbsolutePercentageError
class_docstr_tok: ["It","caculates","diff","=","K.abs","(","(","y","-","x",")","\/","K.clip","(","K.abs","(","y",")",",","K.epsilon","(",")",",","Double.MaxValue",")",")","and","return","100","*","K.mean","(","diff",")","as","outpout",">",">",">","loss","=","MeanAbsolutePercentageError","(",")","creating",":","createZooKerasMeanAbsolutePercentageError"]
code: def __init__(self, bigdl_type="float"):
      super(MeanAbsolutePercentageError, self).__init__(
          None, bigdl_type
      )
  
imports: import sys
  from zoo.pipeline.api.keras.base import ZooKerasCreator
  from bigdl.nn.criterion import Criterion
  from bigdl.util.common import JTensor
label_desc: Use image node_id 1 to create a new MeanAbsolutePercentageError object from inherited base classes: LossFunction with example: obj = MeanAbsolutePercentageError(bigdl_type)